{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Python for Finance Tutorial For Beginners\n",
    "\n",
    "*This notebook was made in preparation for the DataCamp tutorial \"Python for Finance Tutorial for Beginners\"; If you want more explanations on the code or on using Python for Finance, go to the full tutorial [here](https://www.datacamp.com/community/tutorials/finance-python-trading).*\n",
    "\n",
    "The full tutorial covers the following topics:\n",
    "\n",
    "* Getting Started With Python For Finance\n",
    "    - Stocks & Trading\n",
    "    - Time Series Data\n",
    "    - Setting Up The Workspace\n",
    "    - [Python Basics For Finance: Pandas](#basics)\n",
    "        - Importing Financial Data Into Python\n",
    "        - Working With Time Series Data \n",
    "        - Visualizing Time Series Data\n",
    "* [Common Financial Analyses](#commonanalyses)\n",
    "    - Returns\n",
    "    - Moving Windows\n",
    "    - Volatility Calculation\n",
    "    - Ordinary Least-Squares Regression (OLS)\n",
    "* [Building A Trading Strategy With Python](#tradingstrategy)\n",
    "* [Backtesting A Strategy](#backtesting)\n",
    "    - Implementation Of A Simple Backtester\n",
    "    - Backtesting With Zipline And Quantopian\n",
    "* Improving A Trading Strategy\n",
    "* [Evaluating The Trading Strategy](#evaluating)\n",
    "    - Sharpe Ratio\n",
    "    - Maximum Drawdown\n",
    "    - Compound Annual Growth Rate\n",
    "* What now?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "![DataCamp courses](http://community.datacamp.com.s3.amazonaws.com/community/production/ckeditor_assets/pictures/293/content_blog_banner.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The watermark extension is already loaded. To reload it, use:\n",
      "  %reload_ext watermark\n",
      "pandas 0.20.1\n",
      "numpy 1.12.1\n",
      "datetime n\u0007\n",
      "matplotlib 2.0.0\n",
      "pandas_datareader 0.4.1\n",
      "fix_yahoo_finance 0.0.7\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -p pandas,numpy,datetime,matplotlib,pandas_datareader,fix_yahoo_finance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<a id='basics'></a>\n",
    "## Python Basics For Finance: Pandas\n",
    "\n",
    "### Importing Data\n",
    "At this moment, there is a lot going on in the open-source community because of the changes to the Yahoo! Finance API. That's why you don't only use the `pandas_datareader` package, but also a custom fix `fix_yahoo_finance` to get your data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://query1.finance.yahoo.com/v7/finance/download/AAPL?period1=1159653600&period2=1325372400&interval=1d&events=history&crumb=1UHRpKsv.P4\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-10-02</th>\n",
       "      <td>9.689928</td>\n",
       "      <td>9.789278</td>\n",
       "      <td>9.586705</td>\n",
       "      <td>74.860001</td>\n",
       "      <td>9.658961</td>\n",
       "      <td>178159800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>9.606061</td>\n",
       "      <td>9.670574</td>\n",
       "      <td>9.443488</td>\n",
       "      <td>74.080002</td>\n",
       "      <td>9.558321</td>\n",
       "      <td>197677200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>9.560901</td>\n",
       "      <td>9.736376</td>\n",
       "      <td>9.439614</td>\n",
       "      <td>75.380005</td>\n",
       "      <td>9.726055</td>\n",
       "      <td>207270700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>9.616381</td>\n",
       "      <td>9.826696</td>\n",
       "      <td>9.564772</td>\n",
       "      <td>74.829994</td>\n",
       "      <td>9.655093</td>\n",
       "      <td>170970800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>9.602188</td>\n",
       "      <td>9.682185</td>\n",
       "      <td>9.523480</td>\n",
       "      <td>74.220001</td>\n",
       "      <td>9.576384</td>\n",
       "      <td>116739700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Open      High       Low      Close  Adj Close     Volume\n",
       "Date                                                                     \n",
       "2006-10-02  9.689928  9.789278  9.586705  74.860001   9.658961  178159800\n",
       "2006-10-03  9.606061  9.670574  9.443488  74.080002   9.558321  197677200\n",
       "2006-10-04  9.560901  9.736376  9.439614  75.380005   9.726055  207270700\n",
       "2006-10-05  9.616381  9.826696  9.564772  74.829994   9.655093  170970800\n",
       "2006-10-06  9.602188  9.682185  9.523480  74.220001   9.576384  116739700"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas_datareader import data as pdr\n",
    "import fix_yahoo_finance\n",
    "\n",
    "aapl = pdr.get_data_yahoo('AAPL', \n",
    "                          start=datetime.datetime(2006, 10, 1), \n",
    "                          end=datetime.datetime(2012, 1, 1))\n",
    "aapl.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The `pandas_datareader` offers a lot of possibilities to get financial data. If you don't want to make use of this package, however, you can also use Quandl to retrieve data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Ex-Dividend</th>\n",
       "      <th>Split Ratio</th>\n",
       "      <th>Adj. Open</th>\n",
       "      <th>Adj. High</th>\n",
       "      <th>Adj. Low</th>\n",
       "      <th>Adj. Close</th>\n",
       "      <th>Adj. Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-10-02</th>\n",
       "      <td>75.10</td>\n",
       "      <td>75.870</td>\n",
       "      <td>74.30</td>\n",
       "      <td>74.86</td>\n",
       "      <td>25451400.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.690557</td>\n",
       "      <td>9.789914</td>\n",
       "      <td>9.587328</td>\n",
       "      <td>9.659588</td>\n",
       "      <td>178159800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>74.45</td>\n",
       "      <td>74.950</td>\n",
       "      <td>73.19</td>\n",
       "      <td>74.07</td>\n",
       "      <td>28239600.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.606684</td>\n",
       "      <td>9.671201</td>\n",
       "      <td>9.444099</td>\n",
       "      <td>9.557650</td>\n",
       "      <td>197677200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>74.10</td>\n",
       "      <td>75.462</td>\n",
       "      <td>73.16</td>\n",
       "      <td>75.38</td>\n",
       "      <td>29610100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.561521</td>\n",
       "      <td>9.737268</td>\n",
       "      <td>9.440228</td>\n",
       "      <td>9.726687</td>\n",
       "      <td>207270700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>74.53</td>\n",
       "      <td>76.160</td>\n",
       "      <td>74.13</td>\n",
       "      <td>74.83</td>\n",
       "      <td>24424400.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.617007</td>\n",
       "      <td>9.827334</td>\n",
       "      <td>9.565392</td>\n",
       "      <td>9.655717</td>\n",
       "      <td>170970800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>74.42</td>\n",
       "      <td>75.040</td>\n",
       "      <td>73.81</td>\n",
       "      <td>74.22</td>\n",
       "      <td>16677100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.602813</td>\n",
       "      <td>9.682815</td>\n",
       "      <td>9.524101</td>\n",
       "      <td>9.577006</td>\n",
       "      <td>116739700.0</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open    High    Low  Close      Volume  Ex-Dividend  Split Ratio  \\\n",
       "Date                                                                            \n",
       "2006-10-02  75.10  75.870  74.30  74.86  25451400.0          0.0          1.0   \n",
       "2006-10-03  74.45  74.950  73.19  74.07  28239600.0          0.0          1.0   \n",
       "2006-10-04  74.10  75.462  73.16  75.38  29610100.0          0.0          1.0   \n",
       "2006-10-05  74.53  76.160  74.13  74.83  24424400.0          0.0          1.0   \n",
       "2006-10-06  74.42  75.040  73.81  74.22  16677100.0          0.0          1.0   \n",
       "\n",
       "            Adj. Open  Adj. High  Adj. Low  Adj. Close  Adj. Volume  \n",
       "Date                                                                 \n",
       "2006-10-02   9.690557   9.789914  9.587328    9.659588  178159800.0  \n",
       "2006-10-03   9.606684   9.671201  9.444099    9.557650  197677200.0  \n",
       "2006-10-04   9.561521   9.737268  9.440228    9.726687  207270700.0  \n",
       "2006-10-05   9.617007   9.827334  9.565392    9.655717  170970800.0  \n",
       "2006-10-06   9.602813   9.682815  9.524101    9.577006  116739700.0  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import quandl \n",
    "aapl = quandl.get(\"WIKI/AAPL\", start_date=\"2006-10-01\", end_date=\"2012-01-01\")\n",
    "aapl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Alternatively, you can load in a data set that has been retrieved for you already from Yahoo! Finance: \n",
    "aapl = pd.read_csv(\"https://s3.amazonaws.com/assets.datacamp.com/blog_assets/aapl.csv\", header=0, index_col= 0, names=['Open', 'High', 'Low', 'Close', 'Volume', 'Adj Close'], parse_dates=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Working With Time Series Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspect the index \n",
    "aapl.index\n",
    "\n",
    "# Inspect the columns\n",
    "aapl.columns\n",
    "\n",
    "# Select only the last 10 observations of `Close`\n",
    "ts = aapl['Close'][-10:]\n",
    "\n",
    "# Check the type of `ts` \n",
    "type(ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             Open   High    Low      Close       Volume  Adj Close\n",
      "2006-11-01  81.10  81.38  78.36  79.160004  152798100.0  11.308572\n",
      "2006-11-02  78.92  79.32  78.50  78.979996  116370800.0  11.282857\n",
      "2006-11-03  79.36  79.53  77.79  78.290001  107972200.0  11.184286\n",
      "2006-11-06  78.95  80.06  78.43  79.709999  108644200.0  11.387143\n",
      "2006-11-07  80.45  81.00  80.13  80.510002  131483100.0  11.501429\n",
      "             Open   High    Low      Close       Volume  Adj Close\n",
      "2007-01-03  86.29  86.58  81.90  83.800003  309579900.0  11.971429\n",
      "2007-01-04  84.05  85.95  83.82  85.659996  211815100.0  12.237143\n",
      "2007-01-05  85.77  86.20  84.40  85.049995  208685400.0  12.150000\n",
      "2007-01-08  85.96  86.53  85.28  85.470001  199276700.0  12.210000\n",
      "2007-01-09  86.45  92.98  85.15  92.570000  837324600.0  13.224286\n",
      "             Open   High    Low      Close       Volume  Adj Close\n",
      "2006-11-01  81.10  81.38  78.36  79.160004  152798100.0  11.308572\n",
      "2006-11-02  78.92  79.32  78.50  78.979996  116370800.0  11.282857\n",
      "2006-11-03  79.36  79.53  77.79  78.290001  107972200.0  11.184286\n",
      "2006-11-06  78.95  80.06  78.43  79.709999  108644200.0  11.387143\n",
      "2006-11-07  80.45  81.00  80.13  80.510002  131483100.0  11.501429\n",
      "2006-11-08  80.02  82.69  79.89  82.449997  172729200.0  11.778571\n",
      "2006-11-09  82.90  84.69  82.12  83.339996  230763400.0  11.905714\n",
      "2006-11-10  83.55  83.60  82.50  83.120003   93466100.0  11.874286\n",
      "2006-11-13  83.22  84.45  82.64  84.349998  112668500.0  12.050000\n",
      "2006-11-14  84.80  85.00  83.90  85.000000  147238700.0  12.142858\n",
      "2006-11-15  85.05  85.90  84.00  84.050003  163830800.0  12.007143\n",
      "2006-11-16  84.87  86.30  84.62  85.610001  173485200.0  12.230000\n",
      "2006-11-17  85.14  85.94  85.00  85.850006  116606000.0  12.264286\n",
      "2006-11-20  85.40  87.00  85.20  86.470001  142698500.0  12.352858\n",
      "2006-11-21  87.42  88.60  87.11  88.599998  155666700.0  12.657143\n",
      "2006-11-22  88.99  90.75  87.85  90.309998  167985300.0  12.901428\n",
      "2006-11-24  89.53  93.08  89.50  91.630005  129669400.0  13.090000\n",
      "2006-11-27  92.51  93.16  89.50  89.540001  268709000.0  12.791429\n",
      "2006-11-28  90.36  91.97  89.91  91.809998  259043400.0  13.115714\n",
      "2006-11-29  93.00  93.15  90.25  91.799995  289270800.0  13.114285\n",
      "2006-11-30  92.21  92.68  91.06  91.660004  217621600.0  13.094286\n",
      "            Open      Close\n",
      "2006-11-01  81.1  79.160004\n",
      "2006-12-01  91.8  91.320000\n"
     ]
    }
   ],
   "source": [
    "# Inspect the first rows of November-December 2006\n",
    "print(aapl.loc[pd.Timestamp('2006-11-01'):pd.Timestamp('2006-12-31')].head())\n",
    "\n",
    "# Inspect the first rows of 2007 \n",
    "print(aapl.loc['2007'].head())\n",
    "\n",
    "# Inspect November 2006\n",
    "print(aapl.iloc[22:43])\n",
    "\n",
    "# Inspect the 'Open' and 'Close' values at 2006-11-01 and 2006-12-01\n",
    "print(aapl.iloc[[22,43], [0, 3]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              Open    High     Low       Close       Volume  Adj Close\n",
      "2008-12-15   95.99   96.21   93.00   94.750000  222939500.0  13.535714\n",
      "2008-09-09  156.86  159.96  149.79  151.679993  311256400.0  21.668571\n",
      "2009-11-04  190.73  193.85  190.23  190.809998  121882600.0  27.258572\n",
      "2010-01-26  205.95  213.71  202.58  205.940002  466777500.0  29.420000\n",
      "2007-09-17  138.99  140.59  137.60  138.410004  198342900.0  19.772858\n",
      "2010-05-10  250.25  254.65  248.53  253.990005  246076600.0  36.284286\n",
      "2011-11-02  400.09  400.44  395.11  397.410004   81837700.0  56.772858\n",
      "2009-05-04  128.24  132.25  127.68  132.070007  152339600.0  18.867144\n",
      "2007-04-27   98.18   99.95   97.69   99.919998  174850900.0  14.274285\n",
      "2007-08-23  133.09  133.34  129.76  131.069992  216709500.0  18.724285\n",
      "2011-08-09  361.30  374.61  355.00  374.010010  270645900.0  53.430000\n",
      "2008-04-18  159.12  162.26  158.38  161.040009  256691400.0  23.005714\n",
      "2008-10-08   85.91   96.33   85.68   89.790001  551935300.0  12.827143\n",
      "2010-10-18  318.47  319.00  314.29  318.000000  273252700.0  45.428570\n",
      "2011-12-23  399.69  403.59  399.49  403.330017   67349800.0  57.618572\n",
      "2010-05-05  253.03  258.14  248.73  255.989990  220775800.0  36.570000\n",
      "2010-07-22  257.68  260.00  255.31  259.019989  161329700.0  37.002857\n",
      "2011-10-27  407.56  409.00  401.89  404.690002  123666200.0  57.812859\n",
      "2010-08-17  250.08  254.63  249.20  251.970016  105660100.0  35.995716\n",
      "2009-04-27  122.90  125.00  122.66  124.729996  120172500.0  17.818571\n",
      "DatetimeIndexResampler [freq=<MonthEnd>, axis=0, closed=right, label=right, convention=start, base=0]\n"
     ]
    }
   ],
   "source": [
    "# Sample 20 rows\n",
    "sample = aapl.sample(20)\n",
    "\n",
    "# Print `sample`\n",
    "print(sample)\n",
    "\n",
    "# Resample to monthly level \n",
    "monthly_aapl = aapl.resample('M')\n",
    "\n",
    "# Print `monthly_aapl`\n",
    "print(monthly_aapl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Add a column `diff` to `aapl` \n",
    "aapl['diff'] = aapl.Open - aapl.Close\n",
    "\n",
    "# Delete the new `diff` column\n",
    "del aapl['diff']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
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udVkPFlWy7VBJk/OPL97p2d5bUM7g1Fif84UVNZ7tl7/Z71kP1m1Qiu/1qufw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\n4eNNudzttboQwCs3zvKkJO5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At4wx/wbuAk4ELheRlMAWq9vMALYaY14A7gDWAeeLyJCA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\nhTkN9EopFeY00CulVJj7/04a+M0xwplWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x102ca1c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import Matplotlib's `pyplot` module as `plt`\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plot the closing prices for `aapl`\n",
    "aapl['Close'].plot(grid=True)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<a id='commonanalyses'></a>\n",
    "## Common Financial Analysis\n",
    "\n",
    "### Returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            Adj Close\n",
      "2006-10-02   0.000000\n",
      "2006-10-03  -0.010419\n",
      "2006-10-04   0.017549\n",
      "2006-10-05  -0.007296\n",
      "2006-10-06  -0.008152\n",
      "2006-10-09   0.005524\n",
      "2006-10-10  -0.010987\n",
      "2006-10-11  -0.007858\n",
      "2006-10-12   0.027721\n",
      "2006-10-13  -0.003189\n",
      "2006-10-16   0.005065\n",
      "2006-10-17  -0.014721\n",
      "2006-10-18   0.003231\n",
      "2006-10-19   0.059842\n",
      "2006-10-20   0.012153\n",
      "2006-10-23   0.018887\n",
      "2006-10-24  -0.005033\n",
      "2006-10-25   0.007773\n",
      "2006-10-26   0.006244\n",
      "2006-10-27  -0.021657\n",
      "2006-10-30   0.000124\n",
      "2006-10-31   0.008207\n",
      "2006-11-01  -0.023680\n",
      "2006-11-02  -0.002274\n",
      "2006-11-03  -0.008736\n",
      "2006-11-06   0.018138\n",
      "2006-11-07   0.010036\n",
      "2006-11-08   0.024096\n",
      "2006-11-09   0.010794\n",
      "2006-11-10  -0.002640\n",
      "...               ...\n",
      "2011-11-17  -0.019128\n",
      "2011-11-18  -0.006545\n",
      "2011-11-21  -0.015816\n",
      "2011-11-22   0.020325\n",
      "2011-11-23  -0.025285\n",
      "2011-11-25  -0.009319\n",
      "2011-11-28   0.034519\n",
      "2011-11-29  -0.007764\n",
      "2011-11-30   0.024116\n",
      "2011-12-01   0.014992\n",
      "2011-12-02   0.004563\n",
      "2011-12-05   0.008494\n",
      "2011-12-06  -0.005242\n",
      "2011-12-07  -0.004758\n",
      "2011-12-08   0.004035\n",
      "2011-12-09   0.007577\n",
      "2011-12-12  -0.004522\n",
      "2011-12-13  -0.007733\n",
      "2011-12-14  -0.022170\n",
      "2011-12-15  -0.003288\n",
      "2011-12-16   0.005489\n",
      "2011-12-19   0.003123\n",
      "2011-12-20   0.035949\n",
      "2011-12-21   0.001263\n",
      "2011-12-22   0.005297\n",
      "2011-12-23   0.011993\n",
      "2011-12-27   0.007934\n",
      "2011-12-28  -0.009569\n",
      "2011-12-29   0.006159\n",
      "2011-12-30  -0.000296\n",
      "\n",
      "[1323 rows x 1 columns]\n",
      "            Adj Close\n",
      "2006-10-02        NaN\n",
      "2006-10-03  -0.010474\n",
      "2006-10-04   0.017396\n",
      "2006-10-05  -0.007323\n",
      "2006-10-06  -0.008185\n",
      "2006-10-09   0.005509\n",
      "2006-10-10  -0.011048\n",
      "2006-10-11  -0.007889\n",
      "2006-10-12   0.027344\n",
      "2006-10-13  -0.003194\n",
      "2006-10-16   0.005052\n",
      "2006-10-17  -0.014831\n",
      "2006-10-18   0.003225\n",
      "2006-10-19   0.058120\n",
      "2006-10-20   0.012080\n",
      "2006-10-23   0.018711\n",
      "2006-10-24  -0.005046\n",
      "2006-10-25   0.007743\n",
      "2006-10-26   0.006224\n",
      "2006-10-27  -0.021895\n",
      "2006-10-30   0.000124\n",
      "2006-10-31   0.008173\n",
      "2006-11-01  -0.023965\n",
      "2006-11-02  -0.002277\n",
      "2006-11-03  -0.008775\n",
      "2006-11-06   0.017975\n",
      "2006-11-07   0.009986\n",
      "2006-11-08   0.023811\n",
      "2006-11-09   0.010737\n",
      "2006-11-10  -0.002643\n",
      "...               ...\n",
      "2011-11-17  -0.019314\n",
      "2011-11-18  -0.006566\n",
      "2011-11-21  -0.015942\n",
      "2011-11-22   0.020121\n",
      "2011-11-23  -0.025610\n",
      "2011-11-25  -0.009363\n",
      "2011-11-28   0.033936\n",
      "2011-11-29  -0.007794\n",
      "2011-11-30   0.023830\n",
      "2011-12-01   0.014881\n",
      "2011-12-02   0.004552\n",
      "2011-12-05   0.008458\n",
      "2011-12-06  -0.005255\n",
      "2011-12-07  -0.004769\n",
      "2011-12-08   0.004027\n",
      "2011-12-09   0.007548\n",
      "2011-12-12  -0.004532\n",
      "2011-12-13  -0.007763\n",
      "2011-12-14  -0.022420\n",
      "2011-12-15  -0.003293\n",
      "2011-12-16   0.005474\n",
      "2011-12-19   0.003118\n",
      "2011-12-20   0.035318\n",
      "2011-12-21   0.001262\n",
      "2011-12-22   0.005283\n",
      "2011-12-23   0.011922\n",
      "2011-12-27   0.007903\n",
      "2011-12-28  -0.009615\n",
      "2011-12-29   0.006140\n",
      "2011-12-30  -0.000296\n",
      "\n",
      "[1323 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "# Assign `Adj Close` to `daily_close`\n",
    "daily_close = aapl[['Adj Close']]\n",
    "\n",
    "# Daily returns\n",
    "daily_pct_c = daily_close.pct_change()\n",
    "\n",
    "# Replace NA values with 0\n",
    "daily_pct_c.fillna(0, inplace=True)\n",
    "\n",
    "# Inspect daily returns\n",
    "print(daily_pct_c)\n",
    "\n",
    "# Daily log returns\n",
    "daily_log_returns = np.log(daily_close.pct_change()+1)\n",
    "\n",
    "# Print daily log returns\n",
    "print(daily_log_returns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-10-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-02-28</th>\n",
       "      <td>0.125777</td>\n",
       "      <td>0.126451</td>\n",
       "      <td>0.121460</td>\n",
       "      <td>0.122860</td>\n",
       "      <td>0.369611</td>\n",
       "      <td>0.122860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-06-30</th>\n",
       "      <td>0.196030</td>\n",
       "      <td>0.195413</td>\n",
       "      <td>0.198331</td>\n",
       "      <td>0.197735</td>\n",
       "      <td>-0.080296</td>\n",
       "      <td>0.197735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-10-31</th>\n",
       "      <td>0.400961</td>\n",
       "      <td>0.404613</td>\n",
       "      <td>0.392010</td>\n",
       "      <td>0.400796</td>\n",
       "      <td>0.306882</td>\n",
       "      <td>0.400796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-02-29</th>\n",
       "      <td>0.127066</td>\n",
       "      <td>0.130711</td>\n",
       "      <td>0.117746</td>\n",
       "      <td>0.120394</td>\n",
       "      <td>0.172293</td>\n",
       "      <td>0.120394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-06-30</th>\n",
       "      <td>-0.003550</td>\n",
       "      <td>-0.004290</td>\n",
       "      <td>0.005927</td>\n",
       "      <td>0.003673</td>\n",
       "      <td>-0.209762</td>\n",
       "      <td>0.003673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-31</th>\n",
       "      <td>-0.114267</td>\n",
       "      <td>-0.108879</td>\n",
       "      <td>-0.124618</td>\n",
       "      <td>-0.118803</td>\n",
       "      <td>0.133219</td>\n",
       "      <td>-0.118803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-02-28</th>\n",
       "      <td>-0.363639</td>\n",
       "      <td>-0.363388</td>\n",
       "      <td>-0.359305</td>\n",
       "      <td>-0.360865</td>\n",
       "      <td>-0.161601</td>\n",
       "      <td>-0.360865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-06-30</th>\n",
       "      <td>0.312134</td>\n",
       "      <td>0.304359</td>\n",
       "      <td>0.324702</td>\n",
       "      <td>0.316588</td>\n",
       "      <td>-0.386935</td>\n",
       "      <td>0.316588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-10-31</th>\n",
       "      <td>0.421239</td>\n",
       "      <td>0.411193</td>\n",
       "      <td>0.425117</td>\n",
       "      <td>0.415901</td>\n",
       "      <td>-0.158270</td>\n",
       "      <td>0.415901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-28</th>\n",
       "      <td>0.175612</td>\n",
       "      <td>0.176085</td>\n",
       "      <td>0.172864</td>\n",
       "      <td>0.173693</td>\n",
       "      <td>0.170633</td>\n",
       "      <td>0.173693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-06-30</th>\n",
       "      <td>0.223045</td>\n",
       "      <td>0.223317</td>\n",
       "      <td>0.219063</td>\n",
       "      <td>0.223611</td>\n",
       "      <td>0.203680</td>\n",
       "      <td>0.223611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-10-31</th>\n",
       "      <td>0.094380</td>\n",
       "      <td>0.094268</td>\n",
       "      <td>0.099356</td>\n",
       "      <td>0.096125</td>\n",
       "      <td>-0.157478</td>\n",
       "      <td>0.096125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-28</th>\n",
       "      <td>0.221393</td>\n",
       "      <td>0.218082</td>\n",
       "      <td>0.225622</td>\n",
       "      <td>0.221858</td>\n",
       "      <td>-0.230726</td>\n",
       "      <td>0.221858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-06-30</th>\n",
       "      <td>0.034143</td>\n",
       "      <td>0.033863</td>\n",
       "      <td>0.031616</td>\n",
       "      <td>0.031222</td>\n",
       "      <td>-0.043455</td>\n",
       "      <td>0.031222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-31</th>\n",
       "      <td>0.127202</td>\n",
       "      <td>0.133189</td>\n",
       "      <td>0.124572</td>\n",
       "      <td>0.130452</td>\n",
       "      <td>0.429821</td>\n",
       "      <td>0.130452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-02-29</th>\n",
       "      <td>0.013755</td>\n",
       "      <td>0.008387</td>\n",
       "      <td>0.016799</td>\n",
       "      <td>0.011002</td>\n",
       "      <td>-0.404723</td>\n",
       "      <td>0.011002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Open      High       Low     Close    Volume  Adj Close\n",
       "2006-10-31       NaN       NaN       NaN       NaN       NaN        NaN\n",
       "2007-02-28  0.125777  0.126451  0.121460  0.122860  0.369611   0.122860\n",
       "2007-06-30  0.196030  0.195413  0.198331  0.197735 -0.080296   0.197735\n",
       "2007-10-31  0.400961  0.404613  0.392010  0.400796  0.306882   0.400796\n",
       "2008-02-29  0.127066  0.130711  0.117746  0.120394  0.172293   0.120394\n",
       "2008-06-30 -0.003550 -0.004290  0.005927  0.003673 -0.209762   0.003673\n",
       "2008-10-31 -0.114267 -0.108879 -0.124618 -0.118803  0.133219  -0.118803\n",
       "2009-02-28 -0.363639 -0.363388 -0.359305 -0.360865 -0.161601  -0.360865\n",
       "2009-06-30  0.312134  0.304359  0.324702  0.316588 -0.386935   0.316588\n",
       "2009-10-31  0.421239  0.411193  0.425117  0.415901 -0.158270   0.415901\n",
       "2010-02-28  0.175612  0.176085  0.172864  0.173693  0.170633   0.173693\n",
       "2010-06-30  0.223045  0.223317  0.219063  0.223611  0.203680   0.223611\n",
       "2010-10-31  0.094380  0.094268  0.099356  0.096125 -0.157478   0.096125\n",
       "2011-02-28  0.221393  0.218082  0.225622  0.221858 -0.230726   0.221858\n",
       "2011-06-30  0.034143  0.033863  0.031616  0.031222 -0.043455   0.031222\n",
       "2011-10-31  0.127202  0.133189  0.124572  0.130452  0.429821   0.130452\n",
       "2012-02-29  0.013755  0.008387  0.016799  0.011002 -0.404723   0.011002"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Resample `aapl` to business months, take last observation as value \n",
    "monthly = aapl.resample('BM').apply(lambda x: x[-1])\n",
    "\n",
    "# Calculate the monthly percentage change\n",
    "monthly.pct_change()\n",
    "\n",
    "# Resample `aapl` to quarters, take the mean as value per quarter\n",
    "quarter = aapl.resample(\"4M\").mean()\n",
    "\n",
    "# Calculate the quarterly percentage change\n",
    "quarter.pct_change()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            Adj Close\n",
      "2006-10-02        NaN\n",
      "2006-10-03  -0.010419\n",
      "2006-10-04   0.017549\n",
      "2006-10-05  -0.007296\n",
      "2006-10-06  -0.008152\n",
      "2006-10-09   0.005524\n",
      "2006-10-10  -0.010987\n",
      "2006-10-11  -0.007858\n",
      "2006-10-12   0.027721\n",
      "2006-10-13  -0.003189\n",
      "2006-10-16   0.005065\n",
      "2006-10-17  -0.014721\n",
      "2006-10-18   0.003231\n",
      "2006-10-19   0.059842\n",
      "2006-10-20   0.012153\n",
      "2006-10-23   0.018887\n",
      "2006-10-24  -0.005033\n",
      "2006-10-25   0.007773\n",
      "2006-10-26   0.006244\n",
      "2006-10-27  -0.021657\n",
      "2006-10-30   0.000124\n",
      "2006-10-31   0.008207\n",
      "2006-11-01  -0.023680\n",
      "2006-11-02  -0.002274\n",
      "2006-11-03  -0.008736\n",
      "2006-11-06   0.018138\n",
      "2006-11-07   0.010036\n",
      "2006-11-08   0.024096\n",
      "2006-11-09   0.010794\n",
      "2006-11-10  -0.002640\n",
      "...               ...\n",
      "2011-11-17  -0.019128\n",
      "2011-11-18  -0.006545\n",
      "2011-11-21  -0.015816\n",
      "2011-11-22   0.020325\n",
      "2011-11-23  -0.025285\n",
      "2011-11-25  -0.009319\n",
      "2011-11-28   0.034519\n",
      "2011-11-29  -0.007764\n",
      "2011-11-30   0.024116\n",
      "2011-12-01   0.014992\n",
      "2011-12-02   0.004563\n",
      "2011-12-05   0.008494\n",
      "2011-12-06  -0.005242\n",
      "2011-12-07  -0.004758\n",
      "2011-12-08   0.004035\n",
      "2011-12-09   0.007577\n",
      "2011-12-12  -0.004522\n",
      "2011-12-13  -0.007733\n",
      "2011-12-14  -0.022170\n",
      "2011-12-15  -0.003288\n",
      "2011-12-16   0.005489\n",
      "2011-12-19   0.003123\n",
      "2011-12-20   0.035949\n",
      "2011-12-21   0.001263\n",
      "2011-12-22   0.005297\n",
      "2011-12-23   0.011993\n",
      "2011-12-27   0.007934\n",
      "2011-12-28  -0.009569\n",
      "2011-12-29   0.006159\n",
      "2011-12-30  -0.000296\n",
      "\n",
      "[1323 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "# Daily returns\n",
    "daily_pct_c = daily_close / daily_close.shift(1) - 1\n",
    "\n",
    "# Print `daily_pct_c`\n",
    "print(daily_pct_c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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59M0yRR6PbzZVeUvfzCwhLn0zs4S49M3MEuLSNzNLiP+Qa/Ys4S9Mt3p4S9/MLCEufTOz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x107f83a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Adj Close\n",
      "count  1322.000000\n",
      "mean      0.001566\n",
      "std       0.023992\n",
      "min      -0.179195\n",
      "25%      -0.010672\n",
      "50%       0.001677\n",
      "75%       0.014306\n",
      "max       0.139050\n"
     ]
    }
   ],
   "source": [
    "# Import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plot the distribution of `daily_pct_c`\n",
    "daily_pct_c.hist(bins=50)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n",
    "\n",
    "# Pull up summary statistics\n",
    "print(daily_pct_c.describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            Adj Close\n",
      "2006-10-02        NaN\n",
      "2006-10-03   0.989581\n",
      "2006-10-04   1.006946\n",
      "2006-10-05   0.999599\n",
      "2006-10-06   0.991451\n",
      "2006-10-09   0.996928\n",
      "2006-10-10   0.985974\n",
      "2006-10-11   0.978226\n",
      "2006-10-12   1.005343\n",
      "2006-10-13   1.002137\n",
      "2006-10-16   1.007213\n",
      "2006-10-17   0.992386\n",
      "2006-10-18   0.995592\n",
      "2006-10-19   1.055170\n",
      "2006-10-20   1.067994\n",
      "2006-10-23   1.088165\n",
      "2006-10-24   1.082688\n",
      "2006-10-25   1.091103\n",
      "2006-10-26   1.097916\n",
      "2006-10-27   1.074138\n",
      "2006-10-30   1.074272\n",
      "2006-10-31   1.083088\n",
      "2006-11-01   1.057441\n",
      "2006-11-02   1.055036\n",
      "2006-11-03   1.045819\n",
      "2006-11-06   1.064788\n",
      "2006-11-07   1.075474\n",
      "2006-11-08   1.101389\n",
      "2006-11-09   1.113278\n",
      "2006-11-10   1.110339\n",
      "...               ...\n",
      "2011-11-17   5.041545\n",
      "2011-11-18   5.008550\n",
      "2011-11-21   4.929335\n",
      "2011-11-22   5.029522\n",
      "2011-11-23   4.902351\n",
      "2011-11-25   4.856666\n",
      "2011-11-28   5.024313\n",
      "2011-11-29   4.985306\n",
      "2011-11-30   5.105530\n",
      "2011-12-01   5.182074\n",
      "2011-12-02   5.205718\n",
      "2011-12-05   5.249934\n",
      "2011-12-06   5.222415\n",
      "2011-12-07   5.197569\n",
      "2011-12-08   5.218542\n",
      "2011-12-09   5.258082\n",
      "2011-12-12   5.234304\n",
      "2011-12-13   5.193829\n",
      "2011-12-14   5.078681\n",
      "2011-12-15   5.061983\n",
      "2011-12-16   5.089768\n",
      "2011-12-19   5.105664\n",
      "2011-12-20   5.289207\n",
      "2011-12-21   5.295886\n",
      "2011-12-22   5.323938\n",
      "2011-12-23   5.387791\n",
      "2011-12-27   5.430537\n",
      "2011-12-28   5.378574\n",
      "2011-12-29   5.411702\n",
      "2011-12-30   5.410099\n",
      "\n",
      "[1323 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "# Calculate the cumulative daily returns\n",
    "cum_daily_return = (1 + daily_pct_c).cumprod()\n",
    "\n",
    "# Print `cum_daily_return`\n",
    "print(cum_daily_return)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Kl/96O/60oxkAUGTWxz1Pr1XDFwxL7QyRI4bzUqjwGrRqXLG0Uvlenq8rG1rhNQ6p8HLT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\nuweTgLEBDaSjhxBCBAv51zgIFdc2s/pQJW/vKCErKRalZDOLCF6eLg2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7vM/NSzXznYUj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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x107f2b0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import matplotlib\n",
    "import matplotlib.pyplot as plt \n",
    "\n",
    "# Plot the cumulative daily returns\n",
    "cum_daily_return.plot(figsize=(12,8))\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            Adj Close\n",
      "2006-10-31   1.031710\n",
      "2006-11-30   1.140058\n",
      "2006-12-31   1.155110\n",
      "2007-01-31   1.187303\n",
      "2007-02-28   1.145176\n",
      "2007-03-31   1.210302\n",
      "2007-04-30   1.251737\n",
      "2007-05-31   1.453453\n",
      "2007-06-30   1.625638\n",
      "2007-07-31   1.818073\n",
      "2007-08-31   1.734484\n",
      "2007-09-30   1.897943\n",
      "2007-10-31   2.295090\n",
      "2007-11-30   2.333130\n",
      "2007-12-31   2.544817\n",
      "2008-01-31   2.142374\n",
      "2008-02-29   1.671828\n",
      "2008-03-31   1.747569\n",
      "2008-04-30   2.113108\n",
      "2008-05-31   2.468068\n",
      "2008-06-30   2.384260\n",
      "2008-07-31   2.240832\n",
      "2008-08-31   2.285193\n",
      "2008-09-30   1.886767\n",
      "2008-10-31   1.322521\n",
      "2008-11-30   1.254883\n",
      "2008-12-31   1.222865\n",
      "2009-01-31   1.185880\n",
      "2009-02-28   1.256669\n",
      "2009-03-31   1.302498\n",
      "...               ...\n",
      "2009-07-31   1.994633\n",
      "2009-08-31   2.221219\n",
      "2009-09-30   2.374922\n",
      "2009-10-31   2.575893\n",
      "2009-11-30   2.675929\n",
      "2009-12-31   2.657688\n",
      "2010-01-31   2.774716\n",
      "2010-02-28   2.655568\n",
      "2010-03-31   2.984383\n",
      "2010-04-30   3.354910\n",
      "2010-05-31   3.359090\n",
      "2010-06-30   3.488451\n",
      "2010-07-31   3.405691\n",
      "2010-08-31   3.357243\n",
      "2010-09-30   3.658175\n",
      "2010-10-31   4.019961\n",
      "2010-11-30   4.162278\n",
      "2010-12-31   4.294495\n",
      "2011-01-31   4.520171\n",
      "2011-02-28   4.691192\n",
      "2011-03-31   4.641877\n",
      "2011-04-30   4.547362\n",
      "2011-05-31   4.565653\n",
      "2011-06-30   4.422674\n",
      "2011-07-31   4.972456\n",
      "2011-08-31   5.032897\n",
      "2011-09-30   5.243032\n",
      "2011-10-31   5.306305\n",
      "2011-11-30   5.140466\n",
      "2011-12-31   5.248871\n",
      "\n",
      "[63 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "# Resample the cumulative daily return to cumulative monthly return \n",
    "cum_monthly_return = cum_daily_return.resample(\"M\").mean()\n",
    "\n",
    "# Print the `cum_monthly_return`\n",
    "print(cum_monthly_return)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://query1.finance.yahoo.com/v7/finance/download/AAPL?period1=1159653600&period2=1325372400&interval=1d&events=history&crumb=1UHRpKsv.P4\n",
      "https://query1.finance.yahoo.com/v7/finance/download/MSFT?period1=1159653600&period2=1325372400&interval=1d&events=history&crumb=1UHRpKsv.P4\n",
      "https://query1.finance.yahoo.com/v7/finance/download/IBM?period1=1159653600&period2=1325372400&interval=1d&events=history&crumb=1UHRpKsv.P4\n",
      "https://query1.finance.yahoo.com/v7/finance/download/GOOG?period1=1159653600&period2=1325372400&interval=1d&events=history&crumb=1UHRpKsv.P4\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">AAPL</th>\n",
       "      <th>2006-10-02</th>\n",
       "      <td>9.689928</td>\n",
       "      <td>9.789278</td>\n",
       "      <td>9.586705</td>\n",
       "      <td>74.860001</td>\n",
       "      <td>9.658961</td>\n",
       "      <td>178159800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>9.606061</td>\n",
       "      <td>9.670574</td>\n",
       "      <td>9.443488</td>\n",
       "      <td>74.080002</td>\n",
       "      <td>9.558321</td>\n",
       "      <td>197677200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>9.560901</td>\n",
       "      <td>9.736376</td>\n",
       "      <td>9.439614</td>\n",
       "      <td>75.380005</td>\n",
       "      <td>9.726055</td>\n",
       "      <td>207270700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>9.616381</td>\n",
       "      <td>9.826696</td>\n",
       "      <td>9.564772</td>\n",
       "      <td>74.829994</td>\n",
       "      <td>9.655093</td>\n",
       "      <td>170970800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>9.602188</td>\n",
       "      <td>9.682185</td>\n",
       "      <td>9.523480</td>\n",
       "      <td>74.220001</td>\n",
       "      <td>9.576384</td>\n",
       "      <td>116739700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Open      High       Low      Close  Adj Close  \\\n",
       "Ticker Date                                                             \n",
       "AAPL   2006-10-02  9.689928  9.789278  9.586705  74.860001   9.658961   \n",
       "       2006-10-03  9.606061  9.670574  9.443488  74.080002   9.558321   \n",
       "       2006-10-04  9.560901  9.736376  9.439614  75.380005   9.726055   \n",
       "       2006-10-05  9.616381  9.826696  9.564772  74.829994   9.655093   \n",
       "       2006-10-06  9.602188  9.682185  9.523480  74.220001   9.576384   \n",
       "\n",
       "                      Volume  \n",
       "Ticker Date                   \n",
       "AAPL   2006-10-02  178159800  \n",
       "       2006-10-03  197677200  \n",
       "       2006-10-04  207270700  \n",
       "       2006-10-05  170970800  \n",
       "       2006-10-06  116739700  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas_datareader import data as pdr\n",
    "import fix_yahoo_finance\n",
    "\n",
    "def get(tickers, startdate, enddate):\n",
    "    def data(ticker):\n",
    "        return (pdr.get_data_yahoo(ticker, start=startdate, end=enddate))\n",
    "    datas = map (data, tickers)\n",
    "    return(pd.concat(datas, keys=tickers, names=['Ticker', 'Date']))\n",
    "\n",
    "tickers = ['AAPL', 'MSFT', 'IBM', 'GOOG']\n",
    "all_data = get(tickers, datetime.datetime(2006, 10, 1), datetime.datetime(2012, 1, 1))\n",
    "all_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#all_data = pd.read_csv(\"https://s3.amazonaws.com/assets.datacamp.com/blog_assets/all_stock_data.csv\", index_col= [0,1], header=0, parse_dates=[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
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1KnBT8xjg5cCpzW0LcFn/MSVJkqTRWdbFRKrqY0k2tprPAeaa5SuBeeANTftVVVXALUmO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109d57160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "daily_close_px = all_data[['Adj Close']].reset_index().pivot('Date', 'Ticker', 'Adj Close')\n",
    "\n",
    "# Calculate the daily percentage change for `daily_close_px`\n",
    "daily_pct_change = daily_close_px.pct_change()\n",
    "\n",
    "# Plot the distributions\n",
    "daily_pct_change.hist(bins=50, sharex=True, figsize=(12,8))\n",
    "\n",
    "# Show the resulting plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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EgaXjZYsXIep+ZxiG6lrjKFuzttB8k0Sd5NXQmtBp9t5T90Xu04WpVoLtQcZU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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10af47f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a scatter matrix with the `daily_pct_change` data \n",
    "pd.plotting.scatter_matrix(daily_pct_change, diagonal='kde', alpha=0.1,figsize=(12,12))\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Moving Windows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2011-12-16    55.529679\n",
       "2011-12-19    55.491607\n",
       "2011-12-20    55.456536\n",
       "2011-12-21    55.451822\n",
       "2011-12-22    55.444500\n",
       "2011-12-23    55.439643\n",
       "2011-12-27    55.445286\n",
       "2011-12-28    55.437643\n",
       "2011-12-29    55.468393\n",
       "2011-12-30    55.495500\n",
       "Name: Adj Close, dtype: float64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Isolate the adjusted closing prices \n",
    "adj_close_px = aapl['Adj Close']\n",
    "\n",
    "# Calculate the moving average\n",
    "moving_avg = adj_close_px.rolling(window=40).mean()\n",
    "\n",
    "# Inspect the result\n",
    "moving_avg[-10:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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gh9DD4DcQzK0fMkLJ2B6ynf878n/UsqvF4p6LqWlXs8zmqggIQRcIBGWCLMvs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\nR5qTcCpdl0E2GFwIpxj0aasOFHh+f7Nq+vbZ5g6VGkKn1yG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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a3da438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Short moving window rolling mean\n",
    "aapl['42'] = adj_close_px.rolling(window=40).mean()\n",
    "\n",
    "# Long moving window rolling mean\n",
    "aapl['252'] = adj_close_px.rolling(window=252).mean()\n",
    "\n",
    "# Plot the adjusted closing price, the short and long windows of rolling means\n",
    "aapl[['Adj Close', '42', '252']].plot()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Volatility Calculation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KukSyRCLTlZtKpqu51vk6/Ytw2KUZeX+fz9uS6WpUpktEso+CLpEskU5NV+Nr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6AAAg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\nBNleSaTLairby5KSB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lt3mlVH0/l10oAKrZ/cRgOkF/UGIzZHTGZsr2heuqEDMtDzrVXM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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109c09ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the minumum of periods to consider \n",
    "min_periods = 75 \n",
    "\n",
    "# Calculate the volatility\n",
    "vol = daily_pct_change.rolling(min_periods).std() * np.sqrt(min_periods) \n",
    "\n",
    "# Plot the volatility\n",
    "vol.plot(figsize=(10, 8))\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Ordinary Least-Squares Regression (OLS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                   MSFT   R-squared:                       0.281\n",
      "Model:                            OLS   Adj. R-squared:                  0.280\n",
      "Method:                 Least Squares   F-statistic:                     515.5\n",
      "Date:                Tue, 20 Jun 2017   Prob (F-statistic):           1.33e-96\n",
      "Time:                        15:01:37   Log-Likelihood:                 3514.0\n",
      "No. Observations:                1322   AIC:                            -7024.\n",
      "Df Residuals:                    1320   BIC:                            -7014.\n",
      "Df Model:                           1                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const         -0.0005      0.000     -1.119      0.263      -0.001       0.000\n",
      "AAPL           0.4407      0.019     22.704      0.000       0.403       0.479\n",
      "==============================================================================\n",
      "Omnibus:                      268.593   Durbin-Watson:                   2.074\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             7029.493\n",
      "Skew:                          -0.211   Prob(JB):                         0.00\n",
      "Kurtosis:                      14.289   Cond. No.                         41.6\n",
      "==============================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "# Import the `api` model of `statsmodels` under alias `sm`\n",
    "import statsmodels.api as sm\n",
    "from pandas import tseries\n",
    "from pandas.core import datetools\n",
    "\n",
    "# Isolate the adjusted closing price\n",
    "all_adj_close = all_data[['Adj Close']]\n",
    "\n",
    "# Calculate the returns \n",
    "all_returns = np.log(all_adj_close / all_adj_close.shift(1))\n",
    "\n",
    "# Isolate the AAPL returns \n",
    "aapl_returns = all_returns.iloc[all_returns.index.get_level_values('Ticker') == 'AAPL']\n",
    "aapl_returns.index = aapl_returns.index.droplevel('Ticker')\n",
    "\n",
    "# Isolate the MSFT returns\n",
    "msft_returns = all_returns.iloc[all_returns.index.get_level_values('Ticker') == 'MSFT']\n",
    "msft_returns.index = msft_returns.index.droplevel('Ticker')\n",
    "\n",
    "# Build up a new DataFrame with AAPL and MSFT returns\n",
    "return_data = pd.concat([aapl_returns, msft_returns], axis=1)[1:]\n",
    "return_data.columns = ['AAPL', 'MSFT']\n",
    "\n",
    "# Add a constant \n",
    "X = sm.add_constant(return_data['AAPL'])\n",
    "\n",
    "# Construct the model\n",
    "model = sm.OLS(return_data['MSFT'],X).fit()\n",
    "\n",
    "# Print the summary\n",
    "print(model.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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f+VAtKlI9+eTo5y8qUj3gAPcqotq5szvn2muj57Tw52u218mM0ROYo0J9464d\nWadjuVv/zdFa7/oiZuanqKj5YyTB/Q84QPXSS3XxhAmxz7CFfy8pf6ddu7prdO3aot9tPB31fxtY\npGnM6+ms8moQkT2ACz1P1wuqmqAlW4tZCwH7G/bwxhIds0ZEioEdcMH5dM418o18T0hrpWsk4Sqv\n0lLn5vK7LHbu7GIHftfCTp1c3CTYWXHZMvjrX1sk8laKeY4hVFLBkwxlM10B6EQtZ/IU5VRxGrPp\nzJZmrhQCfkZ/sgUE5eXw+ONNc23eegveeouBJSVw6KHRZxjW34vlrWSNdFZ53QQcRmMbHK4SkVJV\n/T9tvPdCoJ+I9MUpgxHAhXHHzATG4GIjw4HnVVVFZCbwkFdjbHegH/BKG+UxMk2+/2MnS3psJn8k\n6SqvAQPg4ovd+9Gj3fiAAdHCj3/9azRmUlcH06enXunlocDLHEElFTzCBXzBzo37yphPOVUMZxrd\nyUG5PV/+RAsMHn/cZcg//rjLVYnbL3V1sYsawvx7sbyVrJBODOU0YKCqNgCIyAPAa0CbFIq6mMgV\nwHO4ZcOT1AX8b8CZVzNxrqwHvaD7lzilg3fco7gAfh3wM7UVXoVBpv6xwwjeJvpGnEb+SMJVXjU1\ncNxx0fNGj3ZjU6a4BMZgsyxwE/Cnn6Zc5fUO+1JFOZVU8C77No735w1X0ZeH6RMTlswhRUXOAnvj\njajyqK2FW2+NJjj6LYw9tLgYyTer1WgR6SgUgO64CR2c2ykUVHU2MDtu7H8C7zcD5yU593+B/w1L\nFqOAaamrKpnySfSNePz41KVakq3yuvnmaLXg2lq3/dxziUur+N/mX3+9iaifsTOPcAFVlPMyRzaO\n785aLuQhKqjkIJaGU56+rYi4umMNDe5ZXHutG/d/N/4qNt81Nngw7L67O2bXXVly4IEcGny2tjqr\n4EhHoYwHXhOR+biFGccQ22PeMHJLS+pzNTdJxVtQQauluBg++AAmToR16xqVzut//SuHbtgQVSaX\nXQYzZ8be96OPEhd9VG3SN/5buvIkQ6mkgucY0ljRdzu+YTjTqKCSMqpjK/rmCxdd5BqBBZW1r6R7\n9Ij2dSkuhiVLYPHixt9DTKa8X3XZb4Wcb3XXjISkVChezseLwJHQ2PDgN6r6SaYFM4y0aUnwNh3l\nE2/B+PkjkyY5ZeJ/w+7c2U2E/fvHuscSWSFlZS73Ihgj6dfP9YVXpZ4inud4Kqngcc5ho9cUtZit\nnMFTjRXTswn+AAAdoUlEQVR9t8llXdbmEi9F4JBDYOzY2PGgkh4wwD3bDz6ItjNOlBDq5/D4zzof\nF3EYTUipULwA+GxVHYALkBtG/tGS4K2vfGpr3UTVo0fs/mQWTHV11F0Dib81+8oqftItKoLu3WNX\nfRUXo/99hyV6cGNF34/ZvfGUI6mhgkrO51F25os2PR5oebXhhOy7L6xenbiCMLjP/fOfp+7E6CuX\nmhp44IHYLwG+heI/R1+ZxJdqMfKWdFxer4rIYaq6sPlDDSNHpBvsLy11pdV/9jOnIOInwGQWTFAR\nxX9r9ifCoKXkB5xVo82kvFVe7z/xKg+90JvKV/rxJtFEvX15pzHpcF/eDfXxhBJjeffdxC2I/cIZ\nqum7phJ9CfCT8eItzuuvd+PZLNVitIp0FMoRQLmIvA9sojGxVw/KqGSGkSnWrYvGLuInwGTus+AE\n2KNHTAylcSIMHrN+vetf4n1r/+r7pUy77l0qp/TgXx//rFGUnnzOCKZSQSWH80p+BNeT4StIVadE\nevd2gfVTT43GRlrimkr2JSBe2YAF5wuEdBTKkIxLYRjZJFXMJdFkFvxmnM5E9sorMGMGtXTiaU6n\n8tJdePpn9Wyp2weALnzHMJ6k/JzvGPLW7ZS8tTTcz5eAlC4vkajVoRrtYR+/tLekxB3nL5P+6CO3\ncu3aa8PPLwo+6+ZW2hl5QzoKZTdguap+A+D1RTkAeD+TghlGxmgu5hL087dwOXLD8Sfy4uZBVHIv\nj3Ee69kRFIrq6jmROVRQydk8QTe+gRlFTXvF+8tu00hwDIWSErcya/Rot+0vPqirc7L5me+RCNx5\np3MPXn89zJ3rZKytddvXXw/jxmVGxnyvsGA0ko5CuRtXy8tnY4Ixwygs0rE2gi15m8mcf/NNqByn\nVG1+kw/4XuMlDuFVKuQhRtw0kN3HjYlVFMEOhhBrKWQDvwpycFXWlCnRpEuR2OrH69a5z3v99a6E\njB9PmjvXbWfKFZXvFRaMRtIqX+8VBwMaa3ulmxBpGPlPokTH+Ja8qs6VNXFiY7zgo5LvMfWSedzz\n7CDeeQfgKAD68D7lVFFOFf15E4YOg/oe8MMfxjadKipqOmknW0HVWppTUOsCPeFramDy5OjxwXL6\nDQ3RFXH+BB+0VNJxRbWlmoGVTikI0lEMq0TkKpxVAnA5NNdU2jAKhOaWCfs0NMCMGXwzcz6P6wVU\n6oU8X388DXdGANhhBzj/2E+poJIfyn8oeuZpr5d6J9cP/qmnnDurpCTqTvrlL+GllxJ3NoRwrBXP\nhaaqSLwbLX7Z9JQp7jn49x40CBYtiq5qCyqfoKWSjisqjKz39tZLpx2SjkK5FPgb8DtcbG8eXn8R\nwyh4mlsmvHkzWzXCPzmZKsqZ0TCM79gGcBV9Tz92PUf1e4UrmE2XB++LFom88043AfuZ9b57a+xY\nl0m+fn1scUhInL9SVOSsFhHo0gW+a2Fi4zXXQPfuvPPFF+w/YYK7lh+3CS6bhliLrFMnF1tZtiy5\nwmiJK6ol1QwSYWVYCoJ0ytd/hleU0TDaHUkCvnpkKa/87WUq7/iCqW8cGFPR95h+H1He/3WGX9qT\nnbrVUX/c2USCCY21ta5y8PXXuwk5mAzZrZu7xzHHpO7OKAJHHw0vvui2VVuuTMAlVI4bx8fV1ew/\nfHhslnrQVQVReUTgJz9xys/PbE+mMNJ1RbU1sN5WhWRkhaQKRUSuVdWbReROEjRnU9WrMiqZYbSV\ndFwkcd+yV+5cStUfoLISVq4c0HjYAdusZtSBS7jwN3vyvXMGgZ/VftllsR0YRWID1WPGxN7vtttg\nw4bmW/2qwn/+k/5qr0ik6TUjkaZLopNlqUNszbJPPnE1yUaPTr16K103VFsD67bSqyBIZaG85b0u\nyoYghhEqLXCRfL5vKY++WkrlL1xIw2fXbt9y4Ya7KaeKQ759DbnoXjhnWOw9gm6ikhJXy8qPO2zZ\n4ibmIHV17jUSib5PRjKlEx9bOfxw15jq3ntjxy+5JP3EwepqV0Hgtdfg73+HGTPc+OTJyXu+t9QN\n1ZbAuq30KgiSKhS/K6OqPpA9cQwjJJpxkXz7rYuTV1bCs89G5/bttnONFSsq4LibzyUy59noNadP\nj11i6wXuBdwk7+dzBCfZXXeNVQB+AcW77oIrrnDyFRU1r1wAdt7ZucFOPRWuuipa8mXJEnfvkpJo\nUL2kxL3W1KR2VcUrhTFjYhVZKvdStt1QttIr70nl8kpZDFJVzwpfHMMIiQQukvp6N+dVVjrd8M03\n7tBIBE4/3XWoHToUttnGu8aqsyGoUM49N+E9GmprKSoO/CvFf/t/4IFoPktDg1MG8+fDCy9Ej1u2\nDO6/38U34q0an3XrYPZsp6ROPRWefNJds77e7auujnaDnD3bxUkeeMDJEyTopopXChCrmFK5l8wN\nZcSRyuVVCnwIPAy8TEj15QwjK3guEp1fzeu9T6Ny+sE8PNxVC/E54ghniZx/PuyyS4Jr+NbI9OlO\nmcSXZQcYM4Z1y5ax86JFsRN4MO5w++1w6aXR7dpaN/HffXdsu9sBA1yXx0T4sZktW5xrq1MnN/HX\n10cnc/8b/PjxzvxKVRreVwK33x6rFEaPdj9Tprjj/dbFKZ6xuaEMn1QKZVfgJGAkrtf708DDqro8\nG4IZRlv44AN46IVSKh8qZXngL3affZwSKS937UiaZezYxIokMDH3gKj1sXmzm4yDE/j06c3nkwQb\nSgURcRO9ajSDXdW5yC65pGkzK0hsOcSXhveVzbp1iZVCusqh0N1QltsSKqliKPXAs8CzItIZp1iq\nReQPqjohWwIaRrqsXw/TpjmX1gsvRMd79IALLoBRo5xVImHY2oGJWfyMd3CT/X33uTjJgAHRhltB\nioujtbPATWrHHps4S14E/vY39/7++6NNunxrIll85Pbbo5ZVqtLwLSl62d6w3JbQaa5jY2fgdJwy\n2QuX4PhE5sUyjPSorXWJ6JWVzsvju/67dHHxkIoKGDIkGqMOjcDErEVFyL77wlvewsj6etdv5eKL\nY9v+ijihrr02duK6+ebUTaueecZV9d2yxQV8LrkktSuqpiZaTv7f/44mLoK5qYJYbkvopArKTwEO\nBGYDf1DVN7ImlWGkoKHBpWhUVcGjj8JXX7lxEfeFs6ICzjnH5RBmjEBrYL3/flixInZ/fb0Ljkci\n0VwSEbfEN37SCgZ24lF1mtJ3qYFzc6Wa+JIVtQzKbhOnLSrIAKkslApcQ62rgask6ifwG2xl8t/V\nMJrw1lvOEqmqgvcDzRMGDnRKZMQI1/MpbVrrPw+e16cPRX5r4ODyYN+yuOYauPVWt9/v3BhPWZkr\nPOkTn2fi9yXx4ynN1cwK5sYUF8fGUIwoZq2FTqoYSlGyfYaRLT7+GKZOdYrk1Vej43vuCRde6BTJ\ngQe24sKt9Z8Hz4tE4LTT0EjELYGMz2qvq3OlT/71r9STVvfuUSVSVBRdBDB5crQ22O23x3aJTEaw\nqKVfQiUYQzFiMWstVKwMvZF3fPONS9T+298O4tVXo/P0DjvAeee5FVrHHNO0N1WLaK3/PHhefT08\n+SRaVAS77w5r18bGS9INepeVuaBPcOluaal7bem353g3TjD4bxgZJicKRUR2Ah7BBfpXA+er6lcJ\njhuDq3IM8Cc/a19EqnGdJP1qeSd7RSyNAmXrVpgzx1kiM2b4dRB3oqQEzjrLWSKnn+7m3VBorf88\nUIXYX8JbVF8Pa9a4/UVFbgXAT36SOnAeJJnrpTXfns2NY+SQXFko1wHzVPUmEbnO2/5N8ABP6fwe\nGIwrTrlYRGYGFE+5qlqdsQJGFRYudEpk6lT4/PPovh/+EA47bAW/+93+7LRTBm7e0ok3GDfxgvFM\nnuwUUjDeMXiwc0/lsoGUuXGMHJErhTIUKPPePwBUE6dQgCHAHFX9EkBE5gCn4DL3jQLm3XddYL2y\nEq/ToeP733eWyIUXQt++UF39MTvttH/mBEl34k0Ub7n7bmeB/PznsQH1Qw+1ydzosORKofRS1Y+9\n958AvRIc0xtX+sVnjTfmM1lE6oHpOHdYlhpxG63hiy/cEt/KSjc/+/Tq5VZnjRrl5uJQkg7DJlm8\nxUsgbDj2WCJ1dc7VZTELowOTMYUiInNx5Vvi+W1wQ1VVRFqqDMpVda2IbI9TKKOAKUnkGIvXYbJX\nr15UZ2G1y8aNG7Nyn7aQDRlra4tYsKAHc+f24uWXd6K+3kXRu3Sp50c/+pyTTvqUQw9dTySifPNN\nbHZ7tmRMh27dunFwcTGiihYX83q3bmwIyFV8443svmIF6wcOZENtbV6uqMqXZ5kKkzEcciqjqmb9\nB1gB7Oa93w1YkeCYkcC9ge17gZEJjvsxMCGd+w4aNEizwfz587Nyn7aQKRnr6lTnzlX98Y9Vt9/e\nLzylGomonnKKalWV6saNuZWxVSxYoHrjje41jtDkTHGPttKsjBm8d7rk1e87CR1VRmCRpjHH5srl\nNRMYA9zkvT6Z4JjngBtFZEdv+2RgnIgUA91V9QsRKQHOAOZmQWYjBa+/7txZDz0Um/h92GEuLnLB\nBc69FSqtSUzM1jktPW/iRFeuxU+AzGZdKatpZYRErhTKTcCjInIR8D5wPoCIDAYuVdWLVfVLEfkj\nsNA75wZvbFvgOU+ZRHDK5L7sfwTjww/h4YedIlm2LDret6/LFamogP0zFVNvzSSY6pxkk38YCZDN\n3aumxjXb8pts+W6zbE3qVtPKCImcKBRVXQeckGB8EXBxYHsSMCnumE3AoEzLaCTm669dEdvKSjfv\n+EshdtrJWSEVFW4uynhwvTWTYLJzUk3+YSRANnevYHY7uFyWbNaVsppWRkhYprzRLFu2uDa5lZUw\nc2a0LFTnznDmmW6F1imnuLkoa7RmEkx2Tiql0dYEyHTuVVbmHmZtrSvnMmFCdi0ES4Y0QsIUipEQ\nVViwwCmRRx+FL7904yJw/PHOpXXuua4cSk5ozSSY7Jxkk7/vmkq3jlaie02JW3yYrB9JIrmy2fzJ\nkiGNEDCFYsTw9tsu6bCqCt57Lzo+YICzREaOhD32yJ18MbS2NInveho/PvmEHlag+oEH3DX81sDp\nllnJVKDcOhQaGcQUisGnn0Yr+i4KFLPp3dspkFGj4KCDcidf6CSbrIMTbHOxk+DEnIxUCZGtjfe0\nBVvNZWQYUygdlO++K2osfzJnTjQm3K0bDB/uguvHHONc+u2OdCbrVLGTuIm52y23JO9z0tpgdyYC\n5baay8gwplA6EHV1MHeuUyLTpx/d2Oq8uDgaXD/jDOjaNbdyZpx0JutUMZq4ibn7kiWJ79OWYHc6\n57bUfWWruYwMYwqlnaMKixe7mMjDDzv3liPCUUc5S+S886Bnz1xKmQZh+v7TneiTuabiJub1Awem\nvldr5U11bmvcV7aay8gwplDaKe+9F63oG2x3vt9+TonsvfdLlJcfmTsBW0ImfP9tnegDE/OGZO11\nMxkAb637ylZzGRnEFEo7Yt06eOwxp0T+85/o+M47u+B6ebkrhSIC1dWbcydoS8lH339wYk5UiC/T\nAXBzXxl5iCmUAue772DWLGeNzJ7tOh8CbLMNnH22s0ZOPNHFSQqWQpw8M60EzX1l5CGFPM10WBoa\nXKn3ykqYNg02bHDjRUUwZIizRM4+G7bbLrdyhkYhTp7ZUILmvjLyDFMoBcSyZdGKvn4Lc4BBg5wl\nMmIE7JqoA017oNAmz0JUgobRRkyh5Dlr1kQr+i5dGh3fay/XKreiAg44IGfiGakoNCVoGG3EFEoe\n8vXX8PjjTonMnx+t6Lvjjq6ib3k5HHWUc3EZhmHkC6ZQ8oQtW+C556IVff2kw86dXbKhX9G3c+fc\nymkYWcVqjxUUplByiKr7f/Er+q5bF91XVubcWeeeC92750xEoy3YZNg2rPZYwWEKJQesWBGt6Ltq\nVXS8f/9oRd8+fXInnxECNhm2nXzMPzJSYgolS3z6KTzyiLNGFi6Mju++u4uJlJe7ir4Z73RoZIdC\nnQzzyaoqxPyjDo4plAyyaRM8+aRTIv/8Z7Si7/bbRyv6HntsO63o29EpxMkw36wqW3pdcJhCCZm6\nOli4cEcmTXIrtTZtcuN+Rd/ycjjrrA5Q0bejU4iTYT5aVbb0uqAwhRICqvDaa/Dgg35F34Mb95WW\nOkvk/PMLoKKvES6FNhkWolVl5BWmUNrA6tXR4Ppbb0XH99jjWy4eso6K7rPY59yBhTWpGB2XQrSq\njLzCFEoL+fLLaEXfF1+Mju+8syt9UlEBkVcmM+jaX7tvev8vD3zRhpEuhWZVGXmFKZQ02LwZnn7a\nKZGnn45W9O3aFYYNc0rkpJOgpMSNr7pvSf75og3DMDKMKZRmeP11txLr66/ddlERnHyyUyLDhrkV\nW/GsHzjQfNGGYXQ4cqJQRGQn4BFgL2A1cL6qfpXguGeBI4EXVfWMwHhfYCrQA1gMjFLVLZmQ9YAD\n3LLeQw5xSmTkSNhtt9TnbOjf33zRhmF0OHJloVwHzFPVm0TkOm/7NwmOuwXYBvj/4sb/DNymqlNF\n5B7gIuDuTAjaqZMLuO+ySwtPNF+0YRgdjFzVqx0KPOC9fwAYluggVZ0HfBMcExEBjgemNXd+WLRY\nmRiGYXRARP3a6Nm8qch6Ve3uvRfgK387wbFlwK98l5eI9AReUtV9ve09gWdU9cAk548FxgL06tVr\n0NSpU8P+OE3YuHEj2+V5u0STMTwKQU6TMRw6qozHHXfcYlUd3NxxGXN5ichcIFH/wN8GN1RVRSRj\nWk1VJwITAQYPHqxlWQiQV1dXk437tAWTMTwKQU6TMRxMxtRkTKGo6onJ9onIpyKym6p+LCK7AZ+1\n4NLrgO4iUqyqdcAewNo2imsYhmG0kVzFUGYCY7z3Y4An0z1RnY9uPjC8NecbhmEYmSFXCuUm4CQR\neQc40dtGRAaLyN/9g0Tk38BjwAkiskZEhni7fgP8QkRW4pYO359V6Q3DMIwm5GTZsKquA05IML4I\nuDiw/aMk568CDs+YgIZhGEaLyZWFYhiGYbQzTKEYhmEYoWAKxTAMwwgFUyiGYRhGKJhCMQzDMELB\nFIphGIYRCqZQDMMwjFAwhWIYhmGEgikUwzAMIxRMoRiGUXjU1MD48e7VyBusp7xhGIVFTQ2ccAJs\n2eJaqs6bZ91R8wSzUAzDKCyqq50yqa93r9XVuZbI8DCFYhhGYVFW5iyTSMS95nnDq46EubwMwygs\nSkudm6u62ikTc3flDaZQDMMoPEpLTZHkIebyMgzDMELBFIphGIYRCqZQDMMwjFAwhWIYhmGEgikU\nwzAMIxRMoRiGYRihIKqaaxmyhoh8DryfhVv1BL7Iwn3agskYHoUgp8kYDh1Vxu+p6s7NHdShFEq2\nEJFFqjo413KkwmQMj0KQ02QMB5MxNebyMgzDMELBFIphGIYRCqZQMsPEXAuQBiZjeBSCnCZjOJiM\nKbAYimEYhhEKZqEYhmEYoWAKpZWIyE4iMkdE3vFed0xwzEARqRGR5SKyVEQuCOzrKyIvi8hKEXlE\nRDrlQkbvuGdFZL2IzIob/4eIvCciS7yfgXkoYz49xzHeMe+IyJjAeLWIrAg8x11ClO0U79orReS6\nBPs7e89lpfec9grsG+eNrxCRIWHJFJaMIrKXiHwXeG735FDGY0TkVRGpE5HhcfsS/t7zTMb6wHOc\nmSkZUVX7acUPcDNwnff+OuDPCY7ZD+jnvd8d+Bjo7m0/Cozw3t8DXJYLGb19JwBnArPixv8BDM/1\nc2xGxrx4jsBOwCrvdUfv/Y7evmpgcAbkigDvAnsDnYDXgR/EHXM5cI/3fgTwiPf+B97xnYG+3nUi\neSbjXsAbmfz7a4GMewEHAVOC/xOpfu/5IqO3b2Omn6OqmoXSBoYCD3jvHwCGxR+gqv9V1Xe89x8B\nnwE7i4gAxwPTUp2fDRk92eYB32Tg/unQahnz7DkOAeao6peq+hUwBzglA7IEORxYqaqrVHULMNWT\nNUhQ9mnACd5zGwpMVdVaVX0PWOldL59kzBbNyqiqq1V1KdAQd262fu9tkTFrmEJpPb1U9WPv/SdA\nr1QHi8jhuG8W7wI9gPWqWuftXgP0zrWMSfhfz113m4h0DlE2n7bImE/PsTfwYWA7XpbJnrvh/4Y4\nWTZ3z5hjvOf0Ne65pXNurmUE6Csir4nICyLyowzIl66MmTi3JbT1Pl1EZJGIvCQimfjSBVjHxpSI\nyFxg1wS7fhvcUFUVkaTL5URkN+BBYIyqNoT55SssGZMwDjeBdsItRfwNcEOeyRgKGZaxXFXXisj2\nwHRgFM4tYaTmY6CPqq4TkUHADBHpr6obci1YAfI9729wb+B5EVmmqu+GfRNTKClQ1ROT7RORT0Vk\nN1X92FMYnyU5rhvwNPBbVX3JG14HdBeRYu8b2R7A2lzJmOLa/rfyWhGZDPwqz2TMp+e4FigLbO+B\ni52gqmu9129E5CGc+yIMhbIW2DPunvGf3z9mjYgUAzvgnls654ZBq2VU5/yvBVDVxSLyLi4uuSgH\nMqY6tyzu3OpQpGp6n1b/vgJ/g6tEpBo4BOctCRVzebWemYC/omMM8GT8Ad6KoyeAKarq+/nx/lHm\nA8NTnZ8NGVPhTZ5+rGIY8Eao0jlaLWOePcfngJNFZEdvFdjJwHMiUiwiPQFEpAQ4g/Ce40Kgn7iV\nbp1wAe34FTxB2YcDz3vPbSYwwlth1RfoB7wSklyhyCgiO4tIBMD7Zt0PF/TOhYzJSPh7zycZPdk6\ne+97AkcDb2ZARlvl1dofnI93HvAOMBfYyRsfDPzde18BbAWWBH4Gevv2xv0DrwQeAzrnQkZv+9/A\n58B3ON/sEG/8eWAZbgKsBLbLQxnz6Tn+1JNjJfATb2xbYDGwFFgO3EGIq6mA04D/4r5t/tYbuwE4\ny3vfxXsuK73ntHfg3N96560ATs3g/0qrZATO9Z7ZEuBV4MwcyniY93e3CWfhLU/1e88nGYGjvP/j\n173XizIlo2XKG4ZhGKFgLi/DMAwjFEyhGIZhGKFgCsUwDMMIBVMohmEYRiiYQjEMwzBCwRSK0eER\nkWEioiLy/TZe5x/xVV6bOf56EVnrlWR5U0RGpinrD9oip2FkClMohgEjgRe912xzm6oOxBX6u9dL\nfkzFMFyl4LTxss8NI+OYQjE6NCKyHfBD4CJc9rE/XiYi/xKRp70eFPeISJG3b6NXLHO5iMwTkZ0T\nXHeQV9BwsYg851cdSIa6qtTf4kqgIyL7iOsBs1hE/i0i3xeRo4CzgFs8q2Yfcb1WBnvn9BSR1d77\nH4vITBF5HpjnfZ5qEZkmIm+LSJVXAQERucmzkJaKyF/a/FCNDospFKOjMxR4VlX/C/hFCH0OB67E\nWQT7AOd449sCi1S1P/AC8PvgBT0r405cT4pBwCTgf1MJISKHAu+oql8nbCJwpXf+r4D/p6oLcOU2\nfq2qA7X54n6HejIc620fAvzc+zx7A0eLSA/gbKC/qh4E/KmZaxpGUswUNjo6I3HlUMD1mBiJK5UC\n8IqqrgIQkYdxlsw0XL+JR7xjKoHH4665P3AgMMczAiK4yrmJuEZEfoIrenimd6/tcOUyHpNoZerW\ntA6Yo6pfBrZfUdU13j2W4BoyvQRsBu4X1w1zVpOrGEaamEIxOiwishOuQdcAryR9BFAR+bV3SHxd\nomR1iuLHBVdHqTQNMW5T1b+IyFm4SX0fnOdgvRdbaY46op6GLnH7NsVt1wbe1wPFqlonrlfPCbjC\njFfgnolhtBhzeRkdmeHAg6r6PVXdS1X3BN4D/EZOh3vVXYuAC3CBe3D/N/5qrgsD4z4rcJ05S8G5\nwESkfypBVHUmriz7GHX9Pt4TkfO880VEDvYO/QbYPnDqasB306W9wszHs4Z2UNXZwDXAwc2cYhhJ\nMYVidGRG4toLBJlOdLXXQmAC8BZO0fjHbsIpmzdw3+Zjmo6pa9E6HPiziLyOq5Z7VBry3AD8wlNg\n5cBF3vnLibZ7nQr8WlwXw32AvwCXichrQM+0PnUs2wOzRGQpTjH+ohXXMAwAqzZsGIkQkTLgV6p6\nRoJ9G1V1u+xLZRj5jVkohmEYRiiYhWIYhmGEglkohmEYRiiYQjEMwzBCwRSKYRiGEQqmUAzDMIxQ\nMIViGIZhhIIpFMMwDCMU/n+UT5GsVwqCRgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109d60160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(return_data['AAPL'], return_data['MSFT'], 'r.')\n",
    "\n",
    "ax = plt.axis()\n",
    "x = np.linspace(ax[0], ax[1] + 0.01)\n",
    "\n",
    "plt.plot(x, model.params[0] + model.params[1] * x, 'b', lw=2)\n",
    "\n",
    "plt.grid(True)\n",
    "plt.axis('tight')\n",
    "plt.xlabel('Apple Returns')\n",
    "plt.ylabel('Microsoft returns')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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h9sEJQhS7gmNqag0aKg82MqG8KBzt4ph3vOTA7A5tmn4PbPpBbzly3YzkGGCj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\n42Q63F3TBKBVsxRF6TEqRTyMY9658+9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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10af47fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "return_data['MSFT'].rolling(window=252).corr(return_data['AAPL']).plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<a id='tradingstrategy'></a>\n",
    "## Building A Trading Strategy With Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Initialize the short and long windows\n",
    "short_window = 40\n",
    "long_window = 100\n",
    "\n",
    "# Initialize the `signals` DataFrame with the `signal` column\n",
    "signals = pd.DataFrame(index=aapl.index)\n",
    "signals['signal'] = 0.0\n",
    "\n",
    "# Create short simple moving average over the short window\n",
    "signals['short_mavg'] = aapl['Close'].rolling(window=short_window, min_periods=1, center=False).mean()\n",
    "\n",
    "# Create long simple moving average over the long window\n",
    "signals['long_mavg'] = aapl['Close'].rolling(window=long_window, min_periods=1, center=False).mean()\n",
    "\n",
    "# Create signals\n",
    "signals['signal'][short_window:] = np.where(signals['short_mavg'][short_window:] \n",
    "                                            > signals['long_mavg'][short_window:], 1.0, 0.0)   \n",
    "\n",
    "# Generate trading orders\n",
    "signals['positions'] = signals['signal'].diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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opdxstB2QUnZ2v3gajUZjYNsY9+KLSU0nI2K5HWeleD4fKhTJYx8bcxOmtYbL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\nJEWkPvpv/3ugLjBNRPp6d1SeQUQeAb5AK8ZEq83Pu6PyXcq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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10776c1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Initialize the plot figure\n",
    "fig = plt.figure()\n",
    "\n",
    "# Add a subplot and label for y-axis\n",
    "ax1 = fig.add_subplot(111,  ylabel='Price in $')\n",
    "\n",
    "# Plot the closing price\n",
    "aapl['Close'].plot(ax=ax1, color='r', lw=2.)\n",
    "\n",
    "# Plot the short and long moving averages\n",
    "signals[['short_mavg', 'long_mavg']].plot(ax=ax1, lw=2.)\n",
    "\n",
    "# Plot the buy signals\n",
    "ax1.plot(signals.loc[signals.positions == 1.0].index, \n",
    "         signals.short_mavg[signals.positions == 1.0],\n",
    "         '^', markersize=10, color='m')\n",
    "         \n",
    "# Plot the sell signals\n",
    "ax1.plot(signals.loc[signals.positions == -1.0].index, \n",
    "         signals.short_mavg[signals.positions == -1.0],\n",
    "         'v', markersize=10, color='k')\n",
    "         \n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<a id='backtesting'></a>\n",
    "## Backtesting A Strategy\n",
    "\n",
    "### Implementation Of A Simple Backtester With Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Set the initial capital\n",
    "initial_capital= float(100000.0)\n",
    "\n",
    "# Create a DataFrame `positions`\n",
    "positions = pd.DataFrame(index=signals.index).fillna(0.0)\n",
    "\n",
    "# Buy a 100 shares\n",
    "positions['AAPL'] = 100*signals['signal']   \n",
    "  \n",
    "# Initialize the portfolio with value owned   \n",
    "portfolio = positions.multiply(aapl['Adj Close'], axis=0)\n",
    "\n",
    "# Store the difference in shares owned \n",
    "pos_diff = positions.diff()\n",
    "\n",
    "# Add `holdings` to portfolio\n",
    "portfolio['holdings'] = (positions.multiply(aapl['Adj Close'], axis=0)).sum(axis=1)\n",
    "\n",
    "# Add `cash` to portfolio\n",
    "portfolio['cash'] = initial_capital - (pos_diff.multiply(aapl['Adj Close'], axis=0)).sum(axis=1).cumsum()   \n",
    "\n",
    "# Add `total` to portfolio\n",
    "portfolio['total'] = portfolio['cash'] + portfolio['holdings']\n",
    "\n",
    "# Add `returns` to portfolio\n",
    "portfolio['returns'] = portfolio['total'].pct_change()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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EVZm7xvFm33/JCN6+7SS6ZmckeVRGUxGvG2100GkKjqVTa18ReR44FcgTkS3A\n3cC9wEsich2wEbjMbf4rnHWVR921/CpVHeuuudwMvAt4gCdVdbnb507gBRH5HbAEmO7KpwPPiMga\nnACFK+KZo2EYiWX2Nzs5WFENwHH9c+nbOSvJIzKaknjdaH8MOq4CNhBQFFFR1ckxLk2M0vYHwA9i\n3OctnOi3cPk6nGi1cHkZjpvPMIxmxPaiQwB4U1NM0bRB4o1GOy3RAzEMo2Wiqvgc1TPmbWD8gM4M\n6xFZ7qq8yqlRc9VxfZtyeEYzoS5X2E9qu66qf2rc4RiG0dL406xvmf7pem44ZSB/muUsuW64N3JJ\n16ds0tNsE2dbpC7LxjI7G4YRk70HK3j4gzUAfkUTC7+ySTVl0xapVdmo6m+aaiCGYbQs9h2sYPQ9\ns+JuX17lBAekp3rqaGm0RuKNRsvA2Wx5FM4+GwBU9doEjcswjGbOc59tqlf7JRv3A5BpbrQ2Sbz/\n6s8A3YGzgY9xNlEWJ2pQhmE0fz5etSvmtWcXhBYhKzpUyWcbnFSJR3Qz73xbJF5lM0hVC4CDqjoT\nZ0PncYkblmEYzYGdxWVc+OhcZsxdT3VN6N7ovaVO1ZFrJ/TnuP6hCUV++drXrNkZ+D26cvsB//Fx\nAzoncMRGcyVeZeOr37pfRI7GSQFjxdMMo5Xx7vJC/vjeKmpcxfLAO6tYsmk/v/n3Cn752tchbcsq\nnTWY75/Qj8euGhNxr1J3AyfAtzscxXPpmF54UiwJe1skXmUzzS10VoCTDmYFVifGMFoVqsp/P/M5\nD3+whsUb96Gq/PPzLf7rz3+2yb/ID1BW6USXZaSlkJvl5ZbTB4Xdz7nnByt38PlGJ9uzudDaLvFm\nEJihqtU46zWHnenZMIzmS2V1wE320uLNrNlZEtFmVWExI3p1BKDctWzS05zosjvOGuIPgwYn1PmF\nRZv5+SvL/LLeuVa7pq0Sr2WzXkSmiYgVIjOMVkpZkNXyyepdPPfZxog2691yztU1SqmrbDLToocy\nl1dVM2Pu+hBZl+z0xhqu0cKIV9kMBd4HbgI2iMhfRaRJas4YhtE0lLtuMYCD5dV0i5KRecbcDQDs\nOFBGdY2S1z4db4xNmtM/Xc+3O0KtI8vy3HaJt8RAqaq+pKoXASOBDjguNcMwWgm+BX+AgxVVbN5X\nCsApR3TBt6a/dPN+Zs7bwJebnT0ztbnFPooSGt21g1k2bZV412wQkVOAy4FJwGLqyPpsGEbLwpdO\nBpzFfZ/1YfZSAAAgAElEQVRV8pcrRtKxnZej736XkvIq7n5jub/dgLz29XqGZQ9ou8Rl2YjIBuB2\n4BNguKpepqr/SuTADMNoWoItGx9ZXg85mWkAZHojFcUJA0P3zLx7+8lR7923czsuHt2rEUZptFTi\nXbMZoaoXqurzqnowng4i8qSI7BSRr4NkuSIyS0RWu9+dXPlQEZkvIuUi8tOw+2wQkWUislREFsdx\nLxGRh0RkjYh8FVb4zTCMGARbNj56dsrEFxN07vD8iOuj+3YKOR/SPZvLx/YOkbXzevjop6fyx8uO\nacTRGi2NeNdsDtTdKoKncFxuwdwFzFbVwcBs9xycipq3An+Ica/TVHWkqo6N417nAIPdz/XAY4cx\ndiNOfv/WN9z1r68idpcbLY/yKJZNr07t/MfjB0bu/O/c3hshW7a1KOT8P7ec6FdYRtslYRnxVHUO\njhIJ5nxgpns8E7jAbbtTVRcRyFQQD1Hv5cqfVocFQEcRifxJZjSYGXPX8/c563hh0WbeXV6Y7OEY\nDeDVJVu48omFEfKeHQMBAP3zIqtrtvdGLvse07uj/3hYfgcGdKnfuo7ROok7QKCR6Kaq293jQqBb\nHH0UeE9EFPi7qk6r4149gc1B/be4su0YjcrH3waijd5bXsh/RXGzGM2fxz5ay33vrIx6rVengLLp\nF1TKuXuHDG6ZOIiUKKln7jpnKPk5GajC5ON6R1w32ibxlhjIAX4NnOSKPgZ+q6pFMTvVgaqqq0Dq\n4kRV3SoiXYFZIrLStZoO514hiMj1OK42+vTpU9/ubR7fBj+AN5dt589XjEriaIzD5dEP18S81qld\nwE0WvJ/mptMH8b0Y5Z1zMtO4deLgxhug0SqI1432JHAAJ9z5Mvd4xmE8b4fPpeV+76yrg6pudb93\nAq8Cx9Zxr61A8M+pXq4s2r2nqepYVR3bpUuXw5hO2+Pjb3dx8v0fcvfrX7N5b6lfXlmt7D1YkcSR\nGYfD1v2H6NExdK/M/1043H88aXj3kGtPTR3HD07szxXjzGIx6ke8brSBqnpx0PlvRGTpYTzvDeAa\n4F73+/XaGotIFpCiqsXu8VnAb+u41xvAzSLyAk4ZhKIgd5tRD8oqq1ENDXn995fb2LS3lJnznVQm\nPXIy2FZUBsDeg+XkZkUuGBvNj2+2H2DqjEUUHijzyx793mgGdmnPkO7ZTD62d9RF/VOHdOXUIZbw\n3ag/8SqbQyJyoqp+CiAiE4BDtXUQkeeBU4E8EdkC3I2jGF4SkeuAjbgbQ0WkO85G0Q5AjYjcDgwD\n8oBX3T/6VOA5VX3HfUTUewFvAf8FrAFKgalxztEIQlUZ+dv3qK5Rvv3dOf4XT3h4bFZ6KkO6ZbNq\nR3FIIkejeXPjs5+HKBqA04d2JcPNc2bRY0ZjE6+yuRGY6a7dCE6U2fdr66Cqk2NcmhilbSGOuyuc\nA0DU4HxV3RPjXoqTw804TFSVm59b4k8hX1ZZ47duDpZXhbTN9HqocpWMhT+3HDbsKY2QZcRIqGkY\njUFcykZVlwLHiEgH9/xw9t0YLYRdJeW8uSzgeSytqPIrm5IwZZOR6qEcZ39GlSmbFkFwTRrDaCpq\nVTYicpWqPisiPwmTA6Cqf0rg2IwksWTT/pDz0opqfNv5wi2bDK+HqhrHAqqqjtyBbjQ/Ssqcf8Ps\n9FT65WWxbGsRl46xVDJGYqnLsvEF1lt5vTbCO18XcsOzn4fIgsv7hiub1BQhNcUJajTLpmVwsNz5\n98xpl8Y/bxjPvLW7OWFgXpJHZbR2alU2qvp39/s3TTMcI9m8/82OCFmFGxRw17++ivD1HzhUSZrH\nUTa2ZtMyKC53EnW0T08lI83D6UPj2VttGA2jLjfaQ7VdV9VbG3c4RrIJzvybm+Vl78EKKqprqKlR\nXlgUSMzgSRGqaxQFUj2OW9Usm5aBz7LJzmjqBCJGW6auTZ2f1/ExWhk9g9KTDOrq5LSqrK7xlwD2\n8evvDKNjuzR+cuYRpLopS2zNpmWwp6QcgA4ZaUkeidGWqMuNNjP4XETau/KS6D2Mlo7HDf64/YzB\nLN6wD3CUTfhazdXj+3H1+H5AoFTwq0u2ctqQrlHzZRnNg3e+3s6N//gCcMoBGEZTEW/xtKNFZAmw\nHFghIp+LyFGJHZqRDHyusMw0D2mue6yyuobisqqYffJznLry//lqOwN+8Zat3TRjbnj2C//x5ZZy\nxmhC4s2NNg34iar2VdU+wB3A44kblpEsfMEAqZ4Uf+LFiqpQy+b+i0eE9Jl4ZGj6kt2um8ZoHuws\nLuPsB+fQ7643/bIBXbLo2zmyZIBhJIp4VwizVPVD34mqfuTmKjNaGb49M16P+KPMKqrVv5lz/IDO\nXBb2i3hgWL2SGjXLpjmgqtz8/BLe/Co0NeDgru15+7aTYvQyjMQQr7JZJyIFwDPu+VXAusQMyUgW\nqsq8NXsA17JxlU1lVQ3FZU64bFZ65J9MeJqTiijlhY2mZc3OYuat3ROhaADS01JI9SSsbqJhRCVe\nZXMt8BvgFZxiZp+4MqMV8fbXhaxza9R0auf1WzaV1TVsL3KUTZfs9Ih+7bymbJobZz04h1hLZ4IF\ncBhNT60/b0TEZ8lMUdVbVXW0qo5R1dtVdV8TjM9oQt5Yus1/fFSPDqSlOi+liuoanv9sEwADu0R6\nTyMsGwuBTiq7S8qjKprxA5ykQ5OPtUKBRtNTl2UzRkR6ANeKyNMQ+pNIVfcmbGRGk1N0qNJ/3KtT\npt+y+dXrywEnl9aVx0W+qDxhoc5m2SSXT1fvjir/29Vj+GrLfiZYahojCdTluP0bMBsYSuSGzsWJ\nHZrRlHy+cR+rdxYDMKJXDiLiX7Px4U1NoZ03+u+TL+8+iyO6+TaBWoBAMvl6q1OtfWjYPpqczDRO\nGtzF9kEZSaFWZaOqD6nqkcCTqjpAVfsHfQY00RiNBFNcVsnFj81jd4lT1vnn5xwJ4LdsfNT2ksrJ\nTPOv55hlkzzeW17IE5+uB+AHJw3g2H65SR6RYTjEG5LSPlwQtJ4TFRF5UkR2isjXQbJcEZklIqvd\n706ufKiIzBeRchH5adh9JonIKhFZIyJ3Bcn7i8hCV/6iiHhdebp7vsa93i/OObZZtuwLLbrq21ke\nrmx+dvaQWu8TCJW2einJIjiR6rH9crlqfF8Azj7Kkm0aySVeZROSLUBEUoExdfR5CpgUJrsLmK2q\ng3Hccz7lsRe4FfhD2HM8wCPAOThloieLyDD38n3Ag6o6CNgHXOfKrwP2ufIH3XZGLWzbH1A2nhQh\nN8sLOCGywVTWsfDvc7tVVJkbLVn4snI/NXUcfTq34zsj8nnz1hP5yxWjkjwyo61TVzTaz0WkGBgh\nIgfcTzGwA3i9tr6qOgdHiQRzPuDLtzYTuMBtu1NVFwGVYe2PBdao6jpVrQBeAM4Xp3rb6cDL4fcK\ne8bLwESxguq1EqxscjIDyRnDEzUe06tjrffxZxywaLSksW6Xk7bQZ52KCEf1yLGSz0bSqWvN5vdA\nDvC0qnZwP9mq2llVf34Yz+umqr5dZoVAXbZ9T2Bz0PkWV9YZ2K+qVWHykD7u9SK3vRGDbUVl/uMJ\ngwKRSh0yA8EAD08exdE9c2q9j8/yecENkzaaHl8Ou+AfDYbRHKjTjaaqNcC4xn6wqirOBtGkISLX\ni8hiEVm8a9euZA4lqfhSzg/sksXvLjjaLw9+YY3sXbtVA/Ducme9YN7aPY08QiMeVhUWU+4GZ2Sk\nmiVjNC/iXbP5QkQaQ+HsEJF8APd7Zx3ttwLBibh6ubI9QEd37ShYHtLHvZ7jto9AVaep6lhVHdul\nS5fDmE7LR1V5afEWAG4744iYbrTwvTTR+P4J/fzHZZUWJNDU/Pczgd0IFt5sNDfiVTbHAfNFZK2I\nfCUiy0Tkq8N43hvANe7xNdSx7gMsAga7kWde4ArgDdcq+hC4JMq9gp9xCfCB296IwtpdB/3H1TWh\nay3Biic1jpfXnZOG+o/X7LSSR02NLxrwyPwOSR6JYUQSb260s+t7YxF5HjgVyBORLcDdwL3ASyJy\nHbARuMxt2x1nk2gHoEZEbgeGqeoBEbkZeBfw4Oz3We4+4k7gBRH5HbAEmO7KpwPPiMganACFK+o7\n9rbExj0BZZMSFkfRIbN+lk2m18N/De/OW8sKWVVYXOcaj9G4lFY41uS0q+sKFDWMpicuZaOqG0Xk\nGMCXl/wTVf2yjj6TY1yaGKVtIY4rLNp93gLeiiJfhxOtFi4vAy6tbWyGg6py3cyA6+Wco/NDrncI\nqlEfrohi0Tu3HQCFB8rqaGk0JpXVNew96GzKtXLPRnMk3kqdtwH/ALq6n2dF5JZEDsxIPJ+tD0Sm\n/+2qMf7QZR/BaejTUuPzuKalOO2sWmdi2Lb/UEgOOx9b9x3iUGU13Tqkh0QRGkZzId6/yuuA41T1\nIICI3AfMBx5O1MCMxPNt0LrKWcOiR6G/8qMTKCmron2UOjbR8LnbqkzZNDq7S8o5408f0yEjjTdu\nnkDXDhn+a77idnnt07FtZUZzJF5lI0BweFE1WFGMlk61uy9m8rF9YkYvje7TqV739AUShAcbGA1n\n6ab9lFZUU1pRzT8/38LFo3tx9p/nUHSokltOHwQQ948Cw2hq4v3LnAEsFJFX3fMLCCzIGy2Ug+6C\ncmNuAPR4fMqm0W5puOxy90MBrN1VwutLt/pdag9/sAZI8sY1w6iFeAME/iQiHwEnuqKpqrokYaMy\nGkR1jSLUvddiV7Hz8urYrvGUjVk2iWP1joDb861l23nli60Rbc4bkR8hM4zmQK3KRkQygBuAQcAy\n4NGgFDFGM0RVufDRuZRVVvPu7SfX6r9fWXgAgCHdsmO2qS8eN0DA1mwanzmrA1kuyiqjK/PThnRt\nquEYRr2oy7KZiZMc8xOczMtHArcnelDG4fP+Nzv5aotTPKvoUCUd23lDrt/3zko8Itxx1hGsLHSK\npQ3NbzxlE7BsTNk0JkWHKv0bZb2elJjJTnt1ymzKYRlG3NSlbIap6nAAEZkOfJb4IRmHS2lFFT98\nOrBv5pvtxYwfGMhBuvdgBY99tBaAH548gP2llWSmeegeFNXUUCwaLTEsc39AjOrTEQG+2LQ/ajuL\nRDOaK3VtnvAH9Jv7rPnj29TnY3ZQIS0IuM0AVmxzjhVt1BeUT9lUW2noRmWtWzpgaPds/nDpMSHX\nvndcH8DWa4zmTV3K5piwOja+ujbFInKgjr5GExO+2W/NrtD8ZKtctxnAn2atAmL7/g8Xs2wah4Xr\n9nD+I3NZtMHZeLt5r1MUrU9uFgO6tGfN/55Dmhv5d/d3juKDO07h4clWIM1ovtTqRlNVy1PegvjF\nK8tCzsMrawYrm0Ub9gEwpm/99tHURapf2Vg0WkN48P1v+XLzfn784lI+vfN0NrnKpneusyaT6knh\ni4IzqalxitYN6BJRud0wmhW2A6yVsGxLEV+6fn0fc9eEVlZYv/sg4fz+ouGNOo52Xuf3yaEKKzHQ\nEBascyyaLfsOsWlPqV/Z9HFzzwFkWw40owURb4kBo5njexmFc/87KwH4ZPUuFq4PrdJ97oh8jmjE\nsGeA9unOC/C9FTt4bUnkPhCjbkorQpdHn5q3wb9m07tTu2hdDKPZY8qmlRAtOSPAox+tZeeBMq6e\nHhlI+JMzj2j0cbQPyhR9+4tL2RcWtGDUzTfbQ5dDn5y7nspqJTs9tVE34BpGU2LKphUw59td/OJV\nZ73mquP7MK5f6DpMuHvNx8AE+PmzM0I9s0u3RA/RNaKzeMNeLn5sftRrXTpYkk2j5ZIwZSMiT4rI\nThH5OkiWKyKzRGS1+93JlYuIPCQia9xKoKOD+lSLyFL380aQvL+ILHT7vOhW8kRE0t3zNe71foma\nY3Ph50GBAUfmd6DgvGEh15/8dH1EH18kU2OTHZYI8j9fbk/Ic1ojRYcqueRvAUUztHuoi7PGIvyM\nFkwiLZungElhsruA2ao6GJjtnoOTnWCw+7keeCyozyFVHel+vhskvw94UFUHAftwyiDgfu9z5Q+6\n7Vo124sO+Y8nDu3GUT1yQmrTHAxbAxjRK4fnf3h8QsbSPsyyWbXDIuTj5af/DK1HeOGoniHnlbZ3\nyWjBJEzZqOocnLLMwZyPkwIH9/uCIPnT6rAA6CgiMXeoieNLOB14Oca9fM94GZgordz30M3NADBh\nUGe6dUjHkyJ8+7tzuHi0U/x02/5DIe3fuPlExvbLTchYMtM8IbnWCovKa2ltBDNrRWAT7r0XDWdE\nr44h1288dWBTD8kwGo2mDn3upqo+v0oh4KvY1RPYHNRuiyvbDmSIyGKgCrhXVV8DOgP7g7Ia+NqH\n3EtVq0SkyG2/OzFTSi6qyp4SZxH+iSnjQnz66WnOb4ndJU2zSD9q1CiWLl0aItsISEFou5EjR7Jk\nSd1Jw8u3l7PiihUMe3EY6d3TG3GkzY8H3l0Zcv6dY3qwJCglzZu3nsiR3Ts09bAMo9FIWoCAqirx\nld/oq6pjgSuBP4tIo/28E5HrRWSxiCzetWtX3R2aEftLK3h/xQ4OVVZTUV1DemoKmV5PRJtwEhnN\nNH78eLxeb61tvF4vJ5xwQlz323DPBvZ/UsTMqxb5N6iWVlRFnVdL5rUlW3nkw7X+8z9eegxZ6an0\n7RwIcz6qR06dJSMMoznT1JbNDhHJV9XtrptspyvfCvQOatfLlaGqvu91bk2dUcC/cFxtqa51428f\ndK8tIpIK5AChuxtdVHUaMA1g7NixLcIhvmjDXn70jy/8tWgmDHISbbbzRiZ76Nc5K+R84tCu3H/J\niISNraCggBkzZtTaxuPxUFBQUGsbcKyaHTN2IAr9Pq7kL8+voNvA9hS8vhyAb347KUK5tlRufzHU\nGvSt1fTObcfLN4z3u0kNoyXT1MrmDeAa4F73+/Ug+c0i8gJwHFDkKqROQKmqlotIHjABuF9VVUQ+\nBC4BXohyr2uA+e71D1wrqlVw47NfsDuoYqMvS0A7b+Q/5a0TB/PoR4FfzCcNzqNz+8S5o/Lz85k6\ndSrTp0+noiLS+khL83L2hVewpjiVNcW1ezWr795GTXUNAohC0Z+289ezAvfcXnSoVaRoCbfS/nDp\nMSEWTKLW1gyjqUmYshGR54FTgTwR2QLcjaNkXhKR63Dc+Ze5zd8C/gtYA5QCU135kcDfRaQGx+V3\nr6qucK/dCbwgIr8DlhAoUz0deEZE1uAEKFyRqDk2NbNW7AhRNMFsDQsCAMhI83DWsG685y48d8qq\n3cXVGNRm3VQpLO50OldNX1jrPXJKhAf+mYm3ynnpplULJy1L5Y0TKilq7/xueG/FDm44peUrm+1F\nZf7jId2yuWRMrySOxjASR8KUjapOjnFpYpS2CtwURT4PiJq8S1XXAcdGkZcBl9ZrsC2E4Fo14fgS\nNIZzqDKQo+yMI7tFbdOYxLJuUjxpDDzxPMaNHFTnPSY8W0mKhuZWE4XvzkvjGde6ufftldxwSsuP\nztpfGsj88Mx1EX/OhtFqsEScrYT3bj8lqjzNE4gByUpvmn/uaNZNujeVOc8/Qvfu3WvtW769nIW3\nLKQmLI9nNOumukb9JQ1aKkWHHOV55rBudLW1GaMVY+lqWjB57b0898Pj+Oz/TYy5WJ6ahJexz7rx\nRaZ5vV6mTp1ap6IBJwJNY+yUF4Xbvg3sPbnjpaW05OW4zzfu5YZnvwAgJ9NynhmtG1M2LYSyIHfY\nv24czzG9cph+zThOGJhH1+zYv4i/P6EfgH+DZ1NRUFBASorz51XfCDStiK5A0qqFAZ9UklPiKNDX\nlm5j6lOLAKd8QqxkpM2V4BxoHU3ZGK0cUzYtAFXl8TnrAOiSnc6Yvrm8fvOJHNO7Yx094YSBeXz2\ni4k8kMCQ52j4rJuUlJRGsWp8SA2cPz/wYv5o1S427y3ltD98xEn3fcCoUaMQkTo/o0Ylt6pl0cZD\n3PVchl9xWjZno7VjyqYF8NGqXfxx1rcAjIpDwYTTtUNGUjYEFhQUcOKJJ8Zl1QAcmH8gplXjQyuU\no3eGvpj/sXCT07+sqtE3liaKVXev5YjNKXx3njMXc6MZrR0LEGgBzJy/wX/8q+8Mi9muuZGfn8/H\nH38cd/txS8ZFlf/h3VX89cM1nDCwM8/98HiufHwBrA1UHf3bx4G9RNfefEejbSxNFOXbyzn4wh5S\nCAQ9dDBlY7RyTNk0czbuOchHqwKpdPJzooc4t2ZuO2Mw/fKyOOWILgD+7AnR+HJvSq0bS71eL1d8\nbwqerE7++9SWprUue7C2HK+xrmz51Tq0Rv0bVv97eXaThKUbRjIxZdOM2V50iFMe+Mh/fu9Fw1t8\nqO/hkOZJCdnsWBi0ETKce/6zgnm//GVM66ayBmaln8gH//t+o48zHnJKhAeeCt2wevRCJXVfNXS3\n/x2N1ov9dTdj3g9KOT+8Zw5XHNsniaNpPvTslMnKwuKY1+duq2bq1Kk8/sR0qioD1o14Uuk8+my6\ndXesiNqipmNdihVqXdtKU3CXS2d7kLDGWq1svGcjRzzS+GW6DaO5YMqmGTNvbSB/6A9O6p/EkTQv\nHpo8ioc/WMPQ7tk88O6qiOtLN++noKCAx6c/GSLP8Kax7PVpcUXGJYLy7eUsvHchNW4Gax9aoRTO\nKKRvQd9WX0rBaLtYNFozZu2uEgBeu2kC54/sWUfrtsMR3bJ5ePKomOHC3tQU8vPzGTjhXPA4v6fq\ns7E0UdQW2u2zbgyjtWLKpplSdKiS1TtL8HpSImrRGw7tw9Lv9HPrv2RnOEqo/5lTEKnfxtJEUdeG\nVZ91U15olU2N1okpm2bK4g17UYURvXLISGsddVsam3OHByqHXzuhP5eNc0oiPTR7NQvX7UEzO5F1\n9ERE4t9Ymiji2bBq1o3RmrE1m2bIm19t56bnnJxZVs8kNqmeFNb//r/Yc7CCzlleHgvab3P5tAUA\n5EyYzLDMA0m1aiD+DatF84qaaESG0bSYsmmG/GX2t/7jK8b1rqWlISLkuQXhLhjZk/vfCQ0YSG2f\ny+tvv0/3nORmVI61YdUw2grmRqsH5dvLWXLKkqh+9c17S7no0bmM//1sPlu/t0HP2bLPKYQ27eox\n9MvLqqO14aNHx+gbXrt1sAgvw0g2CVU2IvKkiOwUka+DZLkiMktEVrvfnVy5iMhDIrJGRL4SkdFB\nfa5x268WkWuC5GNEZJnb5yFxt3PHekZD2XDPBoo+LYrqV7/vnZV8sWk/24vK+MlLS6P0jmTTnlIm\n/vEjnpm/wZ/VubyqmtKKalJThDOH2a7yhjK0e3atu/wNw2gaEm3ZPAVMCpPdBcxW1cHAbPcc4Bxg\nsPu5HngMHMWBU1L6OJzKnHcHKY/HgB8G9ZtUxzMOG180ETVEjRoqraiOehyLmhrl5Ac+ZO2ugxS8\nvpyhBe/Q76432binFID2Gan2kjwMjusfusbVLkadH8MwmpaEKhtVnQOE+5TOB2a6xzOBC4LkT6vD\nAqCjiOQDZwOzVHWvqu4DZgGT3GsdVHWBW1b66bB7RXtGTCqraygsKmNncRl7SsrZd7CCokOVlJRX\nUVpRxdrfBKKJokUN9Q9yd3XNrttt8/W26AvBFzwyF0hO0bPWwC/PDU1U2lTVSQ3DqJ1k/J/YTVW3\nu8eFgM9X1BPYHNRuiyurTb4liry2Z8RkZWExx/9+dtRrOSXCA9MD+ay0QtketuO7vCpgzRyqrNuy\n8a3LhOOzio7M71DnPYxIhvfKCTlvi7nkDKM5ktQAAdciSWhd39qeISLXi8hiEVmcgtI1O5289l5y\ns7zkZKaRnZ5KltfDRQu8Efmsaqpq2PDbgHVTlxttwbo9vLe8EHBS4v/oH05o862nD+Kb307iuR8c\nF9L+4cnJLe7VWli/+2DdjQzDSDjJsGx2iEi+qm53XWE7XflWIDjOt5cr2wqcGib/yJX3itK+tmeE\noKrTgGkAY8eO1c/+3xkRbcq3l7Pwgch8VlIJm5/YRr9fOdbNoSAFU1xWSUVVDd7UFP/5lOmfUVFd\nw9lHdePd5YEEm9+f0J9Mryek6ua1E/rTsV3tBcCM2Bw/IJcF6xzvrW8NzDCM5JIMy+YNwBdRdg3w\nepB8ihuVdjxQ5LrC3gXOEpFObmDAWcC77rUDInK8G4U2Jexe0Z5Rb2rNZ1WjfPsrp1xzsDVTVlnD\n/7z8JQA7i8soLCqjwlVWwYrmxlMHkpvlKJWs9FQ23HsuG+49t0UVSGuOPHHNOL5/Qj8AfnfB0ckd\njGEYAEislOmNcnOR53GskjxgB05U2WvAS0AfYCNwmarudRXGX3EiykqBqaq62L3PtcAv3Nv+r6rO\ncOVjcSLeMoG3gVtUVUWkc7Rn1DbWsWPH6uLFi0Nk5dvLWThgITVlNTF6QUWqkvbBEKa+uQSAM4d1\nY1ZQaYBY3HvRcCsZkGCKSivJiZGs0zCMxkFEPlfVsXW1S6gbTVUnx7g0MUpbBW6KcZ8ngSejyBcD\nET9dVXVPtGfUl3jyWYnCB7ctd+wt4PqTB9SpbHp2zDRF0wSYojGM5oNlEKiFePJZpVULg7Y6/xmv\nGNebcf1ymXfX6Uw6KjTp47Cg6LJ3f3xy4w/WMAyjGWObEGqhrnxW3/3rp3y1xdkvM7pPR+5x1wd6\ndMzkb1ePYVVhMZdPm88tpw/muhP7s3xbEempnojU+IZhGK0de+s1gLu/M4yLH5sPwM2nDyLNE2oo\nDumezdJfneU/P6pH6B4QwzCMtoIpmwYwpm8uH/70VD5ds5vThnRN9nAMwzCaLaZsGkj/vKyQVDWG\nYRhGJBYgYBiGYSQcUzaGYRhGwjFlYxiGYSQcUzaGYRhGwjFlYxiGYSQcUzaGYRhGwkloIs6WhIjs\nwknaebjkAbsbaTgtEZu/zb+tzr8tzx2gr6p2qauRKZtGQkQWx5P5tLVi87f5t9X5t+W51wdzoxmG\nYRgJx5SNYRiGkXBM2TQe05I9gCRj82/btOX5t+W5x42t2RiGYRgJxywbwzAMI+GYsjEMwzASjimb\nevCE6kYAAAZ7SURBVCAio0Wkc7LHkSxEJC3ZY2gOiIgkewxNjYh43O82N3cfImLvywZg//HiQERG\nicj7wELaYA0gETleRF4AHhCRo5M9nqZGRMaLyEMi8n0AbUMLnSIyQURmAr8Ukdy2NHcAETlWRG4F\nUNWaZI+nJWPKphZEJF1E/gY8DjwKzAHOda+1iV94InIp8BjwHyAD+IkrbyvzvwT4K7AImCgiv2sr\nCldEBuD83X8I9AXuEZFzkzuqpkNEbgdexVG057gyT3JH1XIxZVM7+cDnwImq+grwHtBZRKQN/cIb\nDPxbVZ8FHgTHndaG5n8U8IqqPgP8DDgOuFREOiZ3WE3CGOAbVX0KuANYCpwnIr2TOqqmYw1wHnAj\n8HMAVa1uKz+0GhtTNmGIyGUi8lMROVZVN6jq46pa5l5uD/RWVW2tv3Dc+f9ERMa7olXARSLyP8B8\noAfwiIi0yvQcUea/F8gQkRxVLQR24PzKHx/zJi0U1116RJBoEdBLRHqr6j5gLrAfuCgpA0wwUeb/\nJvCV+13ic6cBrfL//URjysZFRDwi8ivgTqAGmC4iF7nXfP+dXgO+KyLtVLU6SUNNCGHzB3hcRL4L\nvALcBpwMTFHVScAu4BIR6Z6c0TY+MeZ/NvAZ0BV4QkRewnnRFAPd3H4t/leuiHQUkTeBWcBlItLe\nvVQGfApc5p6vAlYAuSKS0fQjTQxR5p/lu6Sq1e6PzT8C14lInqpWJW2wLRhTNi6u8hgC3KGqfwLu\nBm4WkSODFgZ3AR8AQ5M0zIQRY/4/Bo5Q1dk4L55VbvPXgRHAwWSMNRFEmf+vcVxHxTgulJeBd1R1\nMk6gyDluv9bgTswC3gVucY9PduW7gAXAcNfSrwa2AhOCrP3WQNT5hwUEfITz3+IWcAIHmnaILZ82\nrWxEZIqInBLkf98BdBKRVHeNZgVweZDLrAQYBKjbv0X/qq1j/v8ClgOTXQtmLXCJ224UjvJp0dQx\n/5eB1cAVqrpXVV9U1SfddkNwrNwWS9DcO6jqVpyUKy/h/LseKyI9XeUyH1gCPOhaPEcBm0SkXdIG\n3wjUMf/jRKSH207A/2Pkd8CdIlIEjG7p//83NW1O2YhDvoh8CFwDfA9nDaI9Tk2K4ThrMwAPAxfi\nuFFQ1b3AHuB097zF/aqt5/z/ClwAVOMER4wTkQXApcAvVLW4ySfQQOo5/4eA80Uk3+07UUSW4yjb\nT5t+9A0jxtwfc11DZapaCrwPdCLwN75DVf+CY809CVwF3Oe2bVEc5vxVRFJEZBDwHM661Ymq+reW\n+P9/UlHVNvMBPO73EcCzPhlOaO+TQEfgHRwzup17/UXg1qB7dEj2PJp4/v8EfuQetweGJ3seSfj3\nv809HghcmOx5NPLcH8aJtgtu+2OcX/E5QHZQ2+xkzyMJ8/f9HXQFTkv2PFryp01sUHTdYPcAHhF5\nC+iA82sddUIZbwa24ywCPgdcgRP2/CJQhfOrDrf9gaYdfcNp4PwrcMK/UdUSYFmTT6CBNMK//wK3\n7Vocd2KLIY653wZsE5FTVPVjt9vjOC/bWUBfERmlqttw1q9aFI00/zGqugXY2fQzaD20ejeaiJyC\n87LshBM3fw9QCZzmW+RTxx/7G+ABVX0ax2U0RUSW4GQMaHEvWB82/7Y7/zjnXoMTDPHroK7nAj8C\nvsSxZLc13agbj0ac/5amG3XrpdWXGBCRk4B+6mzKQ0QexXl5HAJuUdUx4oQ2d8VZo/ixqm52F8Xb\nqeq6ZI29MbD5t93513PuDwH/o6obROR8YJ+qzknW2BuDtj7/5kart2xwftm8FBRRNhfoo86uaI+I\n3OL+uukFVKrqZgBVLWzJL5ogbP5td/71mXu1qm4AUNXXW8mLtq3Pv1nR6pWNqpaqarkGNmGeibN/\nAGAqcKSI/Ad4HvgiGWNMJDb/tjv/w5l7awrnbevzb260iQAB8C8UKs7O7zdccTHwC+BoYL068fat\nEpt/251/feaurdCv3tbn31xo9ZZNEDVAGs5eihHuL5oCoEZVP22tL5ogbP5td/5tee5g828WtPoA\ngWBE5HhgnvuZoarTkzykJsXm33bn35bnDjb/5kBbUza9gKuBP6lqebLH09TY/Nvu/Nvy3MHm3xxo\nU8rGMAzDSA5tac3GMAzDSBKmbAzDMIyEY8rGMAzDSDimbAzDMIyEY8rGMAzDSDimbAzDMIyEY8rG\nMAzDSDimbAzDMIyE8/8BJ+/I/pleFncAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a2f4668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure()\n",
    "\n",
    "ax1 = fig.add_subplot(111, ylabel='Portfolio value in $')\n",
    "\n",
    "# Plot the equity curve in dollars\n",
    "portfolio['total'].plot(ax=ax1, lw=2.)\n",
    "\n",
    "# Plot the \"buy\" trades against the equity curve\n",
    "ax1.plot(portfolio.loc[signals.positions == 1.0].index, \n",
    "         portfolio.total[signals.positions == 1.0],\n",
    "         '^', markersize=10, color='m')\n",
    "\n",
    "# Plot the \"sell\" trades against the equity curve\n",
    "ax1.plot(portfolio.loc[signals.positions == -1.0].index, \n",
    "         portfolio.total[signals.positions == -1.0],\n",
    "         'v', markersize=10, color='k')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<a id='evaluating'></a>\n",
    "## Evaluating Moving Average Crossover Strategy \n",
    "\n",
    "### Sharpe Ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.726876950013\n"
     ]
    }
   ],
   "source": [
    "# Isolate the returns of your strategy\n",
    "returns = portfolio['returns']\n",
    "\n",
    "# annualized Sharpe ratio\n",
    "sharpe_ratio = np.sqrt(252) * (returns.mean() / returns.std())\n",
    "\n",
    "# Print the Sharpe ratio\n",
    "print(sharpe_ratio)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Maximum Drawdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Wf7ZMAUG/5qhXYn4XPYMx5jVU8jNb/iIz5NUU/60u+ZKGWjhPZ/JY/kA8VEe1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\nqmzFxMSjTk5FqRPHh48kms0a92nCsUHrpvteJX2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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ae8e978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define a trailing 252 trading day window\n",
    "window = 252\n",
    "\n",
    "# Calculate the max drawdown in the past window days for each day\n",
    "rolling_max = aapl['Adj Close'].rolling(window, min_periods=1).max()\n",
    "daily_drawdown = aapl['Adj Close']/rolling_max - 1.0\n",
    "\n",
    "# Calculate the minimum (negative) daily drawdown\n",
    "max_daily_drawdown = daily_drawdown.rolling(window, min_periods=1).min()\n",
    "\n",
    "# Plot the results\n",
    "daily_drawdown.plot()\n",
    "max_daily_drawdown.plot()\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Compound Annual Growth Rate (CAGR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.38234456206\n"
     ]
    }
   ],
   "source": [
    "# Get the number of days in `aapl`\n",
    "days = (aapl.index[-1] - aapl.index[0]).days\n",
    "\n",
    "# Calculate the CAGR \n",
    "cagr = ((((aapl['Adj Close'][-1]) / aapl['Adj Close'][1])) ** (365.0/days)) - 1\n",
    "\n",
    "# Print CAGR\n",
    "print(cagr)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
